Thermodynamics and Self Organization..........................................................................................2Properties of dissipative systems......................................................................................................3Complex Systems Terminology.......................................................................................................4Hierarchies of Complex Systems......................................................................................................5Emergence of new levels of complexity in a hierarchically complex dynamic environment..........6
What is life?..........................................................................................................................................8Autopoiesis.......................................................................................................................................8The origin of autopoiesis................................................................................................................10
Evolutionary Epistemology................................................................................................................11Observers........................................................................................................................................11Physics and semiotics.....................................................................................................................11Karl Popper's Epistemology...........................................................................................................13
What is Knowledge?...................................................................................................................13Ontological Domains where Knowledge Can Be Found............................................................15
Forms of evolutionary knowledge..................................................................................................17Origins of embodied knowledge in W2......................................................................................17Codification to preserve knowledge in W3.................................................................................20Two worlds of organismic knowledge or "code duality"............................................................21
The evolution of genetic systems to manage cellular knowledge......................................................24Orders of Autopoiesis.........................................................................................................................26
Is There More Than One Order of Autopoiesis?............................................................................26Second Order Autopoiesis: Multicellular Organisms.....................................................................27Third Order Autopoiesis: Colonies, Societies and Organizations..................................................29
Colonial organisms.....................................................................................................................29Social organisms - the evolution of 'social homeostasis'............................................................29Human economic organizations..................................................................................................31
W.P. HALL KNOWLEDGE AND DIVERSITY IN COMPLEX SYSTEMS 21/05/2023
Emergence and Growth of Knowledge and Diversity in Hierarchically Complex Living Systems - A Sketch
William P. Hall
Summary
An environment conducting a flux of energy and materials between temporally or spatially separated sources and sinks may become more complexly structured due to the emergence of cyclical, dissipative transport systems. Selection favors transport systems able to stabilize themselves against environmental perturbations through feedback. Continuing selection for self-stabilization over long periods of time may eventuate in the emergence of an autopoietic assembly of subsystems (i.e., an autocatalytic set). The stabilizing 'control information' inherent in the instantaneous structure of the autopoietic system represents a form of knowledge that enables the stabilized system to continue an existence as a living and evolving entity. Such self-referential knowledge (defined by Karl Popper as "solutions to problems of life") is integral to the differential survival of nascent autopoietic systems. Maturana and Varela developed the concept of autopoiesis for the autopoietic cybernetics of self-maintenance and self-production. They also equated the cybernetics of autopoiesis with cognition. Concepts of "meaning", "memory", "learning" and "heredity" can also be derived from this framework of Popperian autopoiesis. Hall has argued that autopoiesis has emerged at cellular, (multicellular) organismic, and economic organizational levels. Given an acceptance that different orders of autopoiesis exist, it follows that forms of regulatory knowledge (i.e., solutions to problems of life) exist at each organizational level where autopoiesis occurs. Knowledge may be "tacit", "implicit" or "explicit".
Keywords: autopoiesis, emergence of complexity, origin of life, structural and codified knowledge, evolutionary theory of knowledge, scalar hierarchy theory
Introduction
The philosopher Karl Popper (1972) and the biophysicist Howard Pattee (1995a) independently argued that knowledge or information (knowledge in the broad sense) are evolutionary products of living systems. Throughout this work, I follow Popper in using the term 'knowledge' in a broad, collective sense as an entity's solutions for solving problems of its life (Popper 1972, 1999). The neurobiologists Humberto Maturana and Francisco Varela developed the concept of autopoiesis as a statement of the minimal properties a complex system must have to be considered living (1974, 1980, 1987). Combining the two bodies of work, I argue that knowledge and life are inseparable phenomena - that knowledge cannot exist without life, and that even the most basic kinds of living things cannot exist without forms of knowledge that enable their survival. I explore the basic properties of this conjunction between life and knowledge and discuss why such a conjunction is a necessary consequence of physics. I am not concerned to present a specific physicochemical theory about how life arose on Earth, but rather to explore the more general case of what may be involved in the emergence of complex, self-organizing, self-regulating and self-producing physical systems. However, if the arguments presented here are correct, the framework presented must encompass life on Earth as a particular case, and the general ideas have applications to the origins and evolution of living things over several orders of complexity on the Earth and elsewhere in the Universe.
This paper crosses and amalgamates many disciplines based on my background over four decades, including evolutionary biology, genetics, speciation and the origin of life; a two-year post-doctoral diversion into the epistemology of science (Hall 1983); plus my current professional involvement in
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managing organizational knowledge in a large defense company (Hall 2003a). My thinking has also been greatly influenced by several years of correspondence with Hugo Urrestarazu, a physicist and scientific translator who worked with Humberto Maturana and Franscisco Varela in the formative years when the concept of autopoiesis as a phenomenological definition of life was first developed (Varela et al 1974; Maturana and Varela 1980). From this diversity of ideas, I attempt to reconstruct the primordial origins of knowing entities and the main evolutionary phenomena affecting the growth of knowledge in living things.
The Physical Framework
Thermodynamics and Self Organization
As Prigogine (1955, 1981, 1999, 2000; Prigogine & Antoniou 2000) demonstrated, the convective transport of energy through a fluid medium forces the state of the transport medium away from thermodynamic equilibrium. When looked at spatially, random molecular motion becomes organized into cyclical flows as material carriers physically receive activating quanta of energy from a source and carry them to a sink where they are released. This, of course forces a return flow of the transport medium to the source to pick up more quanta.
Such transport mechanisms may also work over time, to connect a source of activation energy and a temporally separated sink for degraded energy. For example, high-energy photons from the sun activate carrier molecules to a high potential during daylight hours, which may then relax over time through polymerization reactions and radiation of low energy photons to the cold night sky. Morowitz (1968) described in chemical terms how chemical systems can be entropically forced to become more complex - essentially to evolve an increasingly complex 'metabolism' driven by the dissipative transport of photonic energy from the sun to the cold night sky for an overall increase in entropy of the world.
James Kay (1984, 2000) uses the concept of exergy (synonymous with available energy) to clarify discussion of these phenomena. It is recognized that various forms of energy vary in their capacity or quality to do useful work. Some of the quality or capacity of the energy driving that work to perform additional work is irretrievably lost to entropy during any spontaneous physical or chemical process. As stated by Kay (2000) "exergy is a measure of the maximum capacity of the energy content of a system to perform useful work as [the system] proceeds to equilibrium with its surroundings and reflects all the free energies associated with the system".
Kay goes on to define the second law of thermodynamics in these same terms, "during any macroscopic thermodynamic process, the quality or capacity of energy to perform work is irretrievably lost. Energy loses exergy during any real process." A system conducting energy from a source to a sink will be forced away from equilibrium. The system will tend to relax towards the attractor basin represented by thermodynamic equilibrium, and thus will tend to organize itself in ways that maximize the dissipation of extropy along the steepest gradients to approach thermodynamic equilibrium. It should be noted that where the transport medium is complex, dissipation processes will be stochastic rather than deterministic and local contingencies may affect their temporal evolution. Kay argues that the further the system is forced away from equilibrium, the more organizational opportunities it has for dissipating exergy.
As noted above, Prigogine and others showed that random instabilities and fluctuations could lead to bifurcations and new steady-states of the system as defined by attractor basins (Kauffman 1993, etc.) that can be represented by coupled processes stabilized by feedback, such as convection cells, cyclones, cyclical chemical reactions, autocatalytic systems and even living things. Feedback is an
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essential feature for sustained stability that merits a deeper treatment. Complex dynamic systems exhibit two kinds of causal feedback circuits: positive and negative. Negative feedback tends to stabilize some variables within a range of limiting values (oscillatory homeostasis). Positive feedback can either fatally disrupt system organization or lead to chaotic excursions in a phase space that may converge towards strange attractors representing new steady states. Thus, a transient wandering on the edge of chaos caused by turbulence may provide an opportunity to move away from a near equilibrium situation where even small external perturbations could become catastrophic for the continued integrity of the system. The robustness of a system’s resistance to catastrophic perturbations depends strongly on the density of positive feedback circuits affecting each node of its causation network (Thomas & Kaufman 2001, 2003). .
Where such stabilized cyclical systems exhibit coherent self-regulatory behavior, it may be possible to discriminate the systems from their environment as discrete entities. Organization in such dissipative systems normally resides in a zone of the continuum between an area close to thermodynamic equilibrium where energy transport can be achieved by simple radiation and conduction—where nothing interesting happens, and states of very high flux—where ordered feedback is disrupted into chaotic turbulence.
Properties of dissipative systems
Table 1 (from Kay 2000) summarizes the properties of dissipative systems:
Table 1: Properties of Dissipative Systems (after Kay 2000)
Open – exchange material and energy with environment. Nonequilibrium – persist in dynamic steady states away from thermodynamic equilibrium Energy gradients (exergy) between system boundaries maintain nonequilibrium.
Exergy is irreversibly degraded in forming and maintaining organized gradients. Entropy exported to other hierarchical levels
Material or energy cycling - physical transport or chemical cycles are formed to transport material or energy along gradients maintained within systems.
Chaotic and catastrophic behavior - systems may change discontinuously and unpredictably in response to small environmental perturbations
Organized - As dissipative systems are forced away from equilibrium their organization may increase:
- to dissipate more exergy- to become more structured- to exhibit non-linear change as new attractors become accessible- to increasingly resist moving still farther away from equilibrium
Extending ideas of Morowitz (1968), Kay & Schneider (Kay 1984, 2000, 2001; Schneider & Kay 1994, 1994a, 1995) explored how exergy dissipation drives hierarchically complex systems to evolve. They view the Earth as an open thermodynamic system where a large gradient exists between incoming solar radiation and the radiation of heat to outer space. Systems transporting fluxes along parts of that gradient are driven by the second law of thermodynamics to reduce the fluxes by all available physical and chemical processes. Where there are intermediate fluxes of energy, above those that can be dealt with by radiation and conduction and below those that drive the system into chaos (i.e., a 'short circuit'), hyper-cyclic self-organizing processes may evolve to facilitate that dissipation. The selective survival of more effective dissipation paths leads to increasing complexity.
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Complex Systems Terminology
The following definitions derived from Kay (1984) provide a vocabulary for discussing the emergence of complex autopoietic systems.
Complex systems, by definition, are comprised of dynamically interacting components, where different components have different functions relating to the overall system. "Complexity" implies something more than just complicated. In terms of what is physically possible to compute, the detailed dynamics of complex systems are practically incalculable or indeterminate from the detailed properties and positions of their components (Schrodinger 1944; Polanyi 1968; Davies 2004) which is not to say that they are formally uncomputable.
Flux. This refers to the entropically driven transport or flow of energy and matter through an identifiable system. As noted above, the emergence of dynamic complexity is a possible outcome of the dissipation of exergy as energy flows from sources to sinks. Other useful terms include:
Component: a subunit/subsystem carrying out a particular dynamical process within the system. Components are dynamically interconnected by the flow of mass and energy.
Function: The function of a component in a dynamic system is defined by the mass-energy transformation process it performs.
Structure: The structure of a dynamic system is determined by the functions of the interconnected components.
Control structure: Some of the energy flux may be involved in regulatory feedback stabilizing the system around a steady-state away from thermodynamic equilibrium. The interconnections of the components involved in this regulatory feedback forms what Kay defined as the control structure.
Redundancy of function: In some cases, components involved in connections can be removed from the system without seriously affecting the overall dynamics of the system. The component may be able to continue functioning as an entity in its own right only if it is not highly dependant on the system for its microenvironment.
Environment: A system's environment is the set of elements that are not part of the system but may affect it. The environment provides the thermodynamic source of high exergy materials and a sink for degraded materials and heat as exergy dissipates.
Resource/Source: Resources are those elements of material and energy the system requires to transport or incorporate from the environment (i.e., the source) for the system to maintain its dynamic state.
Sink: For an energy flux to exist, allowing the dissipation of exergy to maintain system dynamics, the system must also connect to sinks that are at a higher entropy than the sources.
Hierarchies of Complex Systems
Biological systems are dynamically complex systems, and the problem with complex systems is that complexity may occur at many levels of size. For example, some living systems are themselves part of a larger living system (e.g., cells within a multicellular organism).
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Kay and Schneider adopt Koestler's (1978) concept of Holarchy as an expression of how complexity can be manifested. As discussed in the present work, the holarchy of natural systems comprises the complete hierarchy of complexity–of physical systems and their cybernetic processes (see also Simon 1962; Salthe 1985, 1993; Gould 2002; Lemke 2000, 2000a, 2000b; Lane 2006). The holarchy consists of distinguishable Holons (i.e., systems), such that each holon is always a component of a larger holon (the super system), and is in turn composed of smaller holons (subsystems). This accounts for Koestler's reference to Janus, the two-faced god. One face of the holon always looks inward (downward in scale) to its constituent components that establish possibilities as determined by their capabilities, while the other face always looks outward (upward in scale) to its environment that determines what is allowed by the circumstances at any particular time. Scales (axes) of complexity may be determined along axes of size, time (speed of dynamic interactions), mass, total energy content, etc. (Lemke 2000).
I use the term Entity here in Kolasa & Pickett's (1989) sense as a "primitive term" that cannot be defined within the axiomatic system, where entities may have internal structures consisting of smaller scale entities. The structure of an entity may be comprised of the internal complex of other entities and their static and dynamic interconnections with one another. Following Kay (1984), the observer/analyst determines a level of interest in the hierarchy, and it may be difficult to determine which entities are parts of the system and which parts of the environment.
A related issue is to distinguish between different entities (systems) at the same hierarchical level—the System identification problem. Kay, following Webster (1979), discusses concepts of vertical and horizontal separation in the holarchy. Vertical separation refers to the separation between different scalar levels. "'If we focus on a single level in the hierarchy, higher level behavior occurs so slowly that it is perceived as a constant. Lower level behavior occurs so rapidly that all we observe is a sampled statistical behavior.'" Horizontal separation refers to the separation of presumed systems (entities) at the one scalar level. This "'depends on the isolation of the system making up any level and upon their segregation into groups which form the systems of the next higher level ... some things are more connected than others ... The integrity of a system exists by its high degree of internal interaction.' The stronger the interactions between two systems at one level in the hierarchy, the smaller their horizontal separation."
To determine the boundary of a given system, an observer must select the focal level (Figure 1) for observing the system; then the respective levels containing the environmental super system on one hand, and the level containing the system's components and subsystems on the other hand (Kay 1984; Salthe 1985, 1993; Gould 2002; Lemke 2000, 2000a, 2000b; Lane 2006). The next step is to identify the focal system's Environment at its own level of focus by first eliminating those elements or systems which do not interact dynamically with the focal system. Those that are left form the immediate dynamic environment. The Microenvironment is the environment analyzed at the level of the components and the Macroenvironment is the environment of the supersystem containing the holon.
Kay (1984) considers the utility of reductionist vs holistic approaches for understanding the behaviors of hierarchically complex systems. Reductionism assumes that the behavior of a higher level entity can be fully explained in terms of the behaviors of its subsystems. Polanyi (1968) and Davies (2004) demonstrated the physical incalculability of the higher-level properties of even fairly simple systems, an argument also supported by Ulanowicz (2000, 2002). Kay (1984) argues:
Figure 1. Establishing a level of focus on a system in a hierarchically complex world. (Hall et al. 2005)
The reason we cannot is that we cannot have sufficient information to predict how the components will interact, a priori.... Most of the information we lack is about the past stresses on the system and its components. These stresses have caused the components to EVOLVE certain interactions, which cannot be apparent from simply examining the components at the current moment in time. In short, living systems have "memory" about [or history of] past events and this is reflected in their structure and function. As well the interaction of living system can be probabilistic in nature. However we can explain, a posteriori, the higher level behaviors in terms of the lower level behavior.
Salthe (1985, 1993) and Chaisson (2001) explored in considerable depth the origins and structures of hierarchically complex systems. The behavior of a holon is basically generated by the activities of its components as governed by physical laws, while its trajectory is regulated and constrained by local environmental possibilities provided by its macroenvironment.
Emergence of new levels of complexity in a hierarchically complex dynamic environment.
Salthe (2004) focuses specifically conditions for the emergence of organized systems. Given that today’s world is already complex, new layers of organization will emerge at intermediate levels of complexity in the scalar hierarchy. Between the most fundamental particles and the universe as a whole, entities at all scalar levels are bounded by higher and lower levels. An entity at any level is regulated by conditions provided by the higher scalar levels, while its possible behaviors are generated by capabilities inherent in lower level components. This produces what Salthe (2004:336-337) calls the basic triadic system of scale hierarchies. "The lowermost level of the triad proposes (materially causes), while the uppermost level disposes (mediates what happens at the focal level)..."
One could visualize an endless bubbling up of possibilities as fluctuations from what might come to be the lowest level in a future triad of them after a focal level has emerged with the cohesion of some of those possibilities. Only those possibilities supported by boundary conditions from what would come to be the highest level of the triad could become stabilized for the duration of those boundary conditions -- or even beyond if they become supported by other forms of information (such as genes in cells) as well. In this way, focal level cohesion might evolve from being supported by continued proximate dynamical maintenance by boundary conditions to one involving internal information as well.
Salthe suggests that a new level of complexity (i.e., system) can emerge in an exergy gradient when:
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1. The emergence increases the overall production of entropy of the local supersystem. This is possible only when:
2. The emerging dynamic processes can separate themselves from the existing dynamics of other levels - increasing the rate at which exergy in the flux is dissipated. This happens only if there is a suitable match of
a. boundary conditions and,b. initiating conditions.
The initiating conditions of course must include a large enough local gradient of exergy to fuel emergence of the new system.
Assuming that dynamic processes at different scales proceed at different rates, and assuming that the universe starts in a state of disequilibrium, large-scale processes would take much longer to reach equilibrium from a given starting point, which implies in turn, that systems at different scales would in general exist at different distances from thermodynamic equilibrium.
[U]sing the classical equilibrium approach, it can be seen that there would be no thermodynamic opposition to the formation of new levels generally because a new one would in principle be further from local thermodynamic equilibrium than the lower level which gave rise to it, but closer to its local equilibrium than the upper level that regulated its emergence. Therefore the interpolation of new levels would not change the total entropy of the global system. [Salthe 2004:338]
In the realm of nonequilibrium thermodynamics, the emergence of a new level can be seen as the "cleaning up" or streamlining of energy fluxes to dissipate gradients to heat energy as rapidly as possible (but in most cases a 'short circuit' will not occur because the necessary catalytic conditions for complete dissipation do not exist). However, competition exists between different paths such that those that can consume exergy the fastest will consume the most, creating new, lower quality gradients in the process and possibly "starving" the competing pathways (i.e., systems).
The production of new levels in a scalar hierarchy is here viewed as the way a material system can streamline or linearize its overall energy gradient dissipation rates, this being mandated by the Second Law of thermodynamics which, because of the radical thermodynamic disequilibrium of the Universe, calls for the degradation of energy gradients and the production of physical entropy at the fastest rates possible. The very fastest rates conceivable are not materially possible because of the necessary embodiment of the energy consumers, which requires some portion of the dissipated gradients to be put to work creating and maintaining them. Presumably, without these, often very specialized, consumers, some energy gradients in the Universe would not get dissipated at all. Evolution, then, is the Universe’s devious route to its own negation. [Salthe 2004:339]
However, instabilities in the flux dissipation systems can lead to chaotic flows that substantially reduce flux rates and destabilize the conducting system - leading to its disintegration. The example is the electrical short-circuit that blows the fuse, and thus totally blocks the current flow.
The conclusion here, as amplified in a number of other works, is that for certain spatial and temporal distributions of fluxes between sources and sinks, the second law of thermodynamics may basically cause the world to become more complex through time. The basic properties of matter and energy provide circumstances where complex dynamic systems can emerge spontaneously at a variety of levels of organization within the hierarchy of a complex system. Processes of selection based on maximum entropy production favor systems that can dissipate fluxes faster and more effectively while retaining the necessary structural organization to provide the conduit between sources and sinks. Cyclones and tornados are examples of systems that provide rapid rates of dissipation but are eventually disrupted and disintegrate as the result of minor climatic or geographic perturbations that either reduce the availability of exergy needed to fuel their dynamic structure or exceed their self-regulatory capacity. This is the outcome of a weak mutual interactive
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connectivity between system components within a causation network with little in the way of reciprocal or circular causation loops.
Dynamic systems possessing causation patters based on an interaction network topology with a high number of feedback circuits affecting all components tend to be resistant to disruptive perturbations. When self-regulation conditions are exceeded by perturbations, a high density of negative and positive feedback loops allows the system either to stabilize around oscillatory trajectories between some localized sources and sinks (homeostasis) or to explore quasi-chaotic regions and find more suitable source-sink configurations that absorb that kind of perturbation and thereby avoid disintegration. When this happens, the system is not only self-regulatory (under certain external conditions) but also self-organizing (under changes of those external conditions) (See Thomas and Kaufman, 2001).
What is life?
Autopoiesis
A foundation problem in biology is that there is still no universally accepted definition of what it actually means to be alive, or for how living things can be unambiguously differentiated from the non-living. Many biologists either avoid the question entirely or accept some set of ad hoc descriptors that seem to fit most cases that most people would consider to be living.
To answer questions raised in biology courses they taught, in the late 1960s and 1970s the Chilean neurobiologists Humberto Maturana and Franscisco Varela put together a framework to provide a set of criteria that could be used to diagnose whether a system was living or not (Maturana, 1970, 2002; Varela et al. 1974; Maturana and Varela 1980, 1987). They called this conceptual framework Autopoiesis (literally self + production).
Although Maturana and Varela did their work more or less in isolation from both systems theory and genetically based evolutionary biology, they published their definition, and it has subsequently survived considerable criticism and analysis across a number of disciplines allied to biology, including artificial life and the social sciences. On the other hand, mainstream biologists have largely ignored the works on autopoiesis (Luisi 2003), possibly because Maturana and Varela expressed their concepts in a highly paradigmatic and iteratively defined language1 (Lyon 2004; see Whitaker 2001 for an invaluable guide to this vocabulary). Many biologists working in a scientific realist paradigm would also consider Maturana and Varela's work suspect because of its associations with social theories emerging from the radical constructivist2 and post-modernist philosophies (e.g., Reigler 2001; Salthe 1993). However, as will be shown, Maturana and Varela's ideas can play a central role in understanding biological systems.1 There is a mapping between a physical-cybernetic definition of autopoietic systems and Maturana and Varela’s
explanations based on apparently “recursively” defined distinctions. According to Urrestarazu (pers. comm.) their language (and especially Maturana’s) is not recursive but systematically concerned with the “ontology of observing”, in which attention is focused on what is being said by an observer in contrast with what observers can gather from their experiences in their own domain of existence (“external reality”). This effort to avoid confusion of domains produces an extremely redundant sort of discourse where the basic ontological considerations are being recalled at all levels of analysis, over and over again. It is an iterative language, but not recursive. However, this results in a mode of writing that requires substantial effort to comprehend. Here, I reformulate some of these ideas using Karl Popper's (1972) ontology of three worlds.
2 Though, this is more an effect of hastily conclusions because there are some fundamental differences between constructivism and Maturana’s epistemological stands (Maturana, 1988) with respect to the notion of “external independent reality”, so that he cannot be considered as a genuine constructivist author (Tomm, 1989, Jutoran 1994, 2005). Maturana and Varela do not deny the observers of a cognitive system the capacity to distinguish a “reality” external to what the observed cognitive system itself is capable of “bringing forth as a world” according to the nature of its sensory-motor apparatus. In this, Maturana and Varela's 'constructivism' is very similar to Popper's (1972) stance that all knowledge is internally constructed, but subject to testing and improvement through interactions with the external independent reality.
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Varela et al. (1974) listed six criteria (Hall et al. 2005 summary form), which taken together are necessary for a system or complex entity to be considered as autopoietic or living. Whether they are also sufficient is an issue that has provoked debate among specialists in recent years.3 In abbreviated and paraphrased form, autopoietic entities are:
1) Self-identifiably bounded (demarcated from the environment by membranes, or the entity's components are tagged for self-identification)
2) Individually identifiable components within the boundary (complex)3) Mechanistic (i.e., a system driven by cybernetically regulated exergy fluxes or metabolic
processes)4) System boundaries internally determined (self referential)5) System intrinsically produces own components (self production)6) Self-produced components are necessary and sufficient to produce the system (autonomy).
In a physical sense, an autopoietic system (i.e., a “living” entity) is an autonomously self-regulating and self-producing complex system of dynamic cyclical processes. These cycles are driven and maintained far from thermodynamic equilibrium by the spontaneous transport of fluxes of matter and energy from sources of high exergy through the system to sinks of lower exergy. Such systems are self-organizing and emergent (Salthe 1985, 1993; Schneider & Kay 1994, 1995; Jorgensen 1999; Giampietro et al. 1999; McKelvey 2004). Kauffman (1993) reviewed and summarized a wide variety of mathematical, chemical and biological models demonstrating the emergence of organized (i.e., ordered) structure at the "molecular" level from initially more chaotic or random states. Bourgine and Stewart (2004) proposed a remarkable mathematical model of a 3D tesselation automaton, considered as a minimal example of computer simulated molecular autopoiesis.
Maturana (1970, 2002; Maturana & Varela 1980) stressed in their works that autopoietic systems had to be "circularly closed". According to Whitaker (2001), Circular organization is
[a]n early (and generic) label describing the essentially recursive, cyclical nature of living systems (Cf. circularity). According to Maturana, the notion of this "circular organization" was the conceptual seed for what would later be formally termed autopoiesis (Cf. Maturana, in Maturana & Varela, 1980, p. xvii). The following passage indicates that what was originally termed "circular organization" in essence became the formal term organization :
"Living systems as they exist on earth today are characterized by exergonic metabolism, growth and internal molecular replication, all organized in a closed causal circular process that allows for evolutionary change in the way the circularity is maintained, but not for the loss of the circularity itself. ... This circular organization constitutes a homeostatic system whose function is to produce and maintain this very same circular organization by determining that the components that specify it are those whose synthesis or maintenance it secures. ...Furthermore, this circular organization defines a living system as a unit of interactions and is essential for its maintenance as a unit ..." [my emphasis] (Maturana, 1970b: reprinted in Maturana & Varela, 1980, p. 9)
This concept of closure has been misunderstood by some critics. According to Whitaker 2001:
3 Cameron (2001), Luisi (2003) and Bitbol & Luisi (2004) suggest that the properties of autopoiesis are only necessary in the definition of life. As will be seen in this paper, I assume provisionally that they are also sufficient – as all the present complexity of living things as we know them can emerge naturally from the coming into existence of a minimally autopoietic entity. The entailments of these criteria in terms of the kind of components and the kind of interaction networks that may give raise to the emergence of a cognitive autopoietic system have not been fully analyzed yet. Enactivist authors Bourgine and Stewart (2004) think that these criteria are not sufficient, as they consider that “a system can be autopoietic without being cognitive, and cognitive without being autopoietic” and propose the following thesis: “A system that is both autopoietic and cognitive is a living system.” Urrestarazu considers that there is yet more to say about the way in which the fifth and sixth criteria of Varela et al (1974) should be worded in order to ascertain the autopoietic nature of a system. Maturana and Varela implicitly assume that from the topological configuration of interacting components follows a spatial connectivity giving raise to material interaction structures (forms of compact molecular concatenations occupying a volume in space) that become the physical support for the emergence of cyclical regulatory mechanisms. In a more general (non molecular) autopoietic system, this topological (physical) constraint should be explicitly specified.
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Critics of Maturana and Varela have interpreted the defining closure of autonomous / autopoietic systems to indicate these are "closed systems" in the traditional sense. This is quite simply not the case, and results from (a) a misinterpretation of Maturana and Varela's terminology and (b) inattention to the manner in which the explanatory constructs underlying a traditional ascription of system "openness" (e.g., feedback) are addressed in autopoietic theory.
"Please note that when we speak of organizational closure, by no means do we imply interactional closure, i.e., the system in total isolation. We do assume that every system will maintain endless interactions with the environment which will impinge and perturb it. If this were not so, we could not even distinguish it." (Varela & Goguen, 1978, p. 294, [emphasis in the original])
Maturana and Varela (1980; 1987) provide more extensive discussions of the concept. Hall (2005) observes that these criteria do not consider time as a factor, and argues that for the concept of autopoiesis to be meaningful in real-world contexts, an autopoietic entity must be able to self-maintain its state of autopoiesis over a period of time. They did not extend their definition to include reproduction because they made just the minimal necessary distinctions to describe living entities while they are alive, regardless of the entities' “participation” in the maintenance of trans-generational self-organization, self-production and self-regulation within a species. Their examples of living things that did not and could not reproduce included differentiated nerve cells and bees. As will be shown below, considering what happens to systems meeting the minimal criteria to be considered autopoietic over historical time leads to some interesting conclusions.4
Maturana and Varela also equate the self-regulatory and self-productive aspects of autopoiesis with cognition. Lyon (2004) provides a masterful exposition of this point of view. Van Duijn et al (2005) take a somewhat different view, but still accept that a minimal form of cognition can take place without codified or linguistically expressed knowledge, and give a good example of situational cognition. Borgine and Stewart (2004) distinguish cases of autopoiesis without cognition and of cognition without autopoiesis. Luisi (2003) discusses the difficulties arising from anthropomorphizing the concept of cognition. Bitbol & Luisi (2004) do not accept that cognition can exist without autopoiesis, but do argue that autopoiesis can exist without cognition. However, these variant views depend on how one defines cognition - which is not the purpose of the present paper. As will be discussed below, I follow Maturana and Varela in defining cognition as the sum of the self-regulatory (i.e., homeostatic) processes required to maintain the state of autopoiesis in a fluctuating environment.
Thus, defined in one sentence, autopoiesis in nature (as distinguished from computational models) is the emergent condition achieved by a system of bounded (i.e., self-identifying), self-regulating set of entropically driven (i.e., exergy dissipating) dynamic processes able to produce and maintain the system’s autonomous existence in the face of environmental perturbations; i.e., that which qualifies a complex dynamic entity as "living".
What, then, is required to turn a newly emergent system passively driven by an energy flux at an intermediate level of organization into an actively self-identifying, self-maintaining and self-producing autopoietic system? The first part of the answer comes from physics, the second from philosophy.
However, the physics and the philosophy are entangled because both the question and the answer involve us as observers. A realist physicist would argue that if autopoiesis is to be considered as an objective phenomenon occurring in nature, it pre-existed before any kind of philosophy, since (human) philosophers are just a particular kind of living organism evolved from amongst uncountable other species without philosophizing capabilities. That “What” cannot be avoided as a 4 In fact, if we take evolution as an outcome of the “successful transmission” of autopoietic capabilities, generation
after generation, we are talking of a higher order complex phenomenon: self-maintenance of autopoiesis through time. As will be seen in the following discussion, interesting things happen as autopoietic entities survives and change through historical time.
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scientific question and thermodynamic considerations are not sufficient in themselves to provide the solution. As any physicist would expect, the second law of thermodynamics should apply to any material system, autopoietic systems included. But the material conditions leading to the establishment of autopoietic behavior are special and cannot be derived from a statistical theory that accounts only for global states—even if the analysis is refined to localized levels like attractor basins of entropy stabilization. There is something peculiar to molecular dynamics that allows the emergence of cyclically maintained interaction mechanisms capable of generating new emerging levels of self-sustained complexity. What these peculiarities are will be elaborated in the following sections. The emergence of compensating mechanisms relies on these peculiar characteristics of macromolecular interactivity that facilitated the origin of the first autopoietic systems on Earth. All other kinds of systems I consider here to be autopoietic5 emerged in the subsequent evolutionary history of the growing complexity of macromolecular systems.
Evaluating explanations of the origin of autopoiesis
In this paper I seek to present an argument for the physicochemical origin of life itself, under circumstances that existed billions of years ago that cannot be reconstructed to any degree of determinable accuracy. My thesis can only be evaluated on the basis of the plausibility of the claimed processes and the ability to survive logical analysis and testing of arguments about general or universal phenomena as required in the claimed processes. Rizzotti (1994), following Deamer and Fleishacker (1994), discussed some of the factors that should be considered in determining the plausibility of a thesis regarding an evolutionary process. These are (1) the explanation does not require any major discontinuity in process (i.e., it occurs gradually), (2) that the process can take place without a need for "isolated special cases", and (3) that the expected outcome of the process is more "robust" than others. Robustness means, (a) the overall yield of the expected products should be reasonably high, (b) the process should be simple, "in the sense that every chemical system must be compatible with the resumed primordial situation...", such that the proposed processes do not depend on sophisticated media or reagents available only in the lab; and (c) that can occur in a "random" way, i.e., where there are a variety of thermodynamically equivalent paths for steps that does not require kinetic biases due to requirements for a specific catalyst.
I believe that the argument presented in the remainder of this paper meets these criteria.
Evolutionary Epistemology
Observers
Maturana and Varela’s definition of autopoiesis hinges on the concept of an autopoietically cognitive entity or "Observer" able to discriminate entities and boundaries (minimally its own identity and boundaries) in its environment. This is one of Maturana and Varela's paradigmatically more difficult terms to define in neutral language (see Whittaker 2001 - http://www.enolagaia.com/EA.html#observer). At least in the intersubjective case, an observer is a cognitive subject or entity able to discriminate things and respond to or codify those observations in a way that is meaningful to itself or other subjects. This definition will be filled out more in discussions below. The central argument of Maturana is that the observer, while attempting to explain cognition (or autopoiesis), cannot avoid considering the fact that he or she is also structured as a molecular cognitive autopoietic system and thereby both subject and object in the act of explaining the very phenomenon to be explained.
5 In the world we know first-hand, special aspects of carbon-based macromolecular dynamics favored the emergence of autopoiesis. However, in other regimes of temperature, pressure, etc. it may be possible that very different kinds of autopoiesis could emerge - still driven by the conduction of energy fluxes from sources to sinks.
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Physics and semiotics
The key to understanding the origins of autopoiesis is to understand where and how the complex system comes to discriminate 'self' from non-self and acquires the capacity to control the self. Howard Pattee in a series of works beginning in 1969 has explored these fundamental questions from a viewpoint beginning in biophysics (Pattee 1995, 1995a, 1996, 1997, 2000, 2001, 2001a). His student, Luis Rocha has continued the work (Rocha 1997, 1998, 2001; Rocha & Bollen 2001; Rocha & Hordijk 2005).
Pattee (1996) introduces the concept of Epistemic Operations, which include biological functions like Observation, Detection, Recognition, Measurement and Control, that he considers differentiate living things from non-life. Defining this set of terms at this point presupposes that we already have a clear understanding of how these concepts follow from physical processes in the autopoietic framework. For this reason, we will accept them for now as 'primitive', and allow their physical definitions to emerge from the development of the paper.
Pattee also uses three important epistemological concepts in developing his concept of epistemic operations may be relatively unfamiliar. Like Maturana and Varela's writing, Pattee's writing tends towards circularity in its definitions. Following are my interpretations of these terms. All assume the involvement of an observer and that which is observed.
Epistemic cut refers to the strict ontological separation (in physical and philosophical senses) between
knowledge of reality from reality itself, e.g., description from construction, simulation from realization, mind from brain [or cognition from physical system]. Selective evolution began with a description-construction cut.... The highly evolved cognitive epistemology of physics requires an epistemic cut between reversible dynamic laws and the irreversible process of measuring initial conditions. This is also known as the measurement problem." (Pattee 1995a).
Semiotic control (Pattee 1997) refers to the situation where symbolically encoded information is used to control a physical process. In other words there is an epistemic cut between the control information and that which is controlled that is the reciprocal to the kinds of cuts cited immediately above (see also Corning 2001, 2002). By contrast to physical laws that are global and inexorable, controls are local and conditional. According to Pattee (2000):
Physical laws and semiotic controls require disjoint, complementary modes of conceptualization and description. Laws are global and inexorable. Controls are local and conditional. Life originated with semiotic controls. Semiotic controls require measurement, memory, and selection, none of which are functionally describable by physical laws that, unlike semiotic systems, are based on energy, time, and rates of change. However, they are structurally describable in the language of physics in terms of nonintegrable constraints, energy degenerate states, temporal incoherence, and irreversible dissipative events.
Local and conditional control is determined by the historically developed instantaneous structure of the physical ensemble including both what is controlled and what is providing the controlling constraints. Control is an effect of the instantaneous dynamics of the structure of local situation as this constrains the possibilities allowed by universal law.
Still following Pattee (2000), at its core, physical theory does not include a capability to control. Universal physical laws specifically relate to situations where there is no control where the relationship between cause and effect "is invariant with respect to different observers, and consequently those relationships between events over which the observer has no control." For control to exist, the 'controller' [which may be no more than the instantaneous local ensemble itself] must be able to provide some form of local circumstances or local structural constraint (which may be positive or negative) in addition to what is dictated/expected by universal physical law.
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Semantic closure provides a connection between the semantic/cognitive processes of recognition, measurement and decision and the application of constraints (controls) to the physical world. Semantic closure
[i]s an extension of von Neumann's logic of description and construction for open-ended evolution. Semantic closure is both physical and logical, and it is an apparently irreducible closure, which is why the origin of life is such a difficult problem. [Pattee (2000)]
Semantic closure is presumably what Maturana and Varela were trying to express in their concept of "circular" closure. However, Pattee (2000) did not see a clear path by which semantic closure could evolve from an unthinking world of purely physical processes.
Semantic closure refers to the situation where there is a cyclic process of self-reference between the material and symbolic aspects of the organism relating (1) to the physical processes of observation and detection, (2) the semantic processes of recognition, measurement and decision, (3) the physical application of semiotic controls, and (4) observation of the results of that application to begin a new cycle. An example of this is Boyd's OODA loop process (Boyd, 1976; Hall, 2003, 2005; Hall et al. 2005) - Figure 2. Maturana and Varela (1980, etc) use the concept of Cognition for the semantically closed cybernetics of autopoietic self-regulation and self-maintenance/production.
AO
OBSERVE(Results of Test)
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RESULTS OF ACTI ONS
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DNA GENETIC
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Figure 2. John Boyd's OODA Loop concept (from Hall 2003, after Boyd 1976 - see http://www.belisarius.com)
A Symbol is some form of abstracted code that has a semantic significance by providing some kind of control information in a particular environment. Pattee (2001a) notes that symbols are energy-degenerate and rate-independent codes separated by an epistemic cut from the rate dependent dynamics of the physical structures that they are used to control. Although Pattee's construction provides a good starting point, it is incomplete. As discussed in the next section, Karl Popper's epistemology distinguishes two ontologically significant epistemic cuts between the pure physical dynamics and encoded control information.
The Meaning of the symbols is determined by the effect of that control information.
It should be noted that Biosemiotics is the study of the physics and philosophy of symbolic codification systems. Where biophysical applications are concerned, Pattee was probably the intellectual founder of the discipline. It has been substantially extended by Søren Breier (1995,
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1996, 1998, 1999, 2001, 2003, 2003a), Klaus Emmeche (1997, 1997a, 1998, 2000, 2002, 2004; Emmeche & Hoffmeyer 1991; Emmeche et al. 1997, 2000) and Jesper Hoffmeyer (1997, 2001, 2001a, 2002, 2002a; Hoffmeyer & Emmeche 1991). However, it is beyond the scope of the present work to go very far down this path.
Karl Popper's Epistemology
What is Knowledge?
Recognition, decision and measurement assume the existence of something to measure against and decide in relation to, which here is termed "Knowledge". Pattee argues that knowledge is a codified product of life. The concept of codification implies too much, and as used by Pattee, leaves a large gap of understanding between the lifeless systems of uncontrolled physics and living systems that are complicated enough to symbolically store an evolved knowledge in a nucleic acid-based genetic system that enables them to control aspects of their internal organization and the external world.
Karl Popper (1934, 1963, 1966, 1968, 1972, 1974, 1974a, 1978, 1982, 1994; Popper and Eccles 1977) and Donald T. Campbell (1960, 1990, 1990a, etc - as reviewed by McKelvey 1999 and McKelvey & Baum 1999) have developed a biologically based epistemology that supports an exploration of the earliest stages in the emergence of control information (knowledge). Here, I follow Popper, whose expression of the concepts is the most clear.
Many scientists and philosophers are familiar with Popper's early works, The Logic of Scientific Discovery (1934/1959) and Conjectures and Refutations (1963). In these, he argued that it was impossible to deductively prove that mental claims about reality were true. Following Tarski, Popper defined Truth as "correspondence with reality". In this early work Popper argued that a single falsification of a deductive inference from a theory/claim was sufficient to falsify the claim. He further argued that because truth could not be proved but falsity could be, the best way we could improve the quality of our knowledge was to make bold hypotheses to include the maximum number of connections with the world and work strenuously to criticize or refute the connections. Those hypotheses that survived refutation were more adequate representations of the world than those that were refuted. (Hall 1983).
Popper, in his later works (1968, 1972, 1974, 1974a, 1978, 1982, 1994, 1999; Popper and Eccles 1977), responding to critics of the earlier works, also accepted that falsification could not deductively prove the falsity of a hypothesis. Any hypothesis can be "immunized" against falsification by an infinite regress of auxiliary hypotheses introduced to defend the original hypothesis against particular falsifications. However, Popper (1972 et seq.) argues that it is possible to approach a correspondence with reality through cycles of hypothesis construction and criticism - an approach adopted by the critical rationalist school of philosophy.
In the 1972 book, Objective Knowledge, published in his 70th year, Popper related his approach to natural selection and evolution, and formalized it as his "general theory of evolution".
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TS1TS2•••••
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Figure 3. Popper's "general theory of evolution" (after Popper 1972: pp. 243). I add the inferred iteration loop to the drawing. Pn is a problem situation the living entity faces in the world, TSm represent a range of tentative solutions the entity may attempt or propose in order to solve the problem. EE represents a process of criticism and error elimination that selectively removes those solutions that don't work in practice. Pn+1
represents the now changed problem situation remaining after the first one is solved. As the entity iterates the process, it will construct an increasingly accurate representation of external reality.
Elsewhere Popper abbreviates this evolutionary theory of knowledge to the "tetradic schema", P1 → TT → EE → P2, where TT is rendered as "tentative theories" rather than TS, "tentative solutions". This latter construction is appropriate for discussing criticism of linguistically expressed theories rather than embodied solutions. Based on this biological point of view, Popper then defines knowledge as "solutions to problems", and notes that "all life is problem solving" (Popper 1999).
Campbell (1960, 1990, 1990a) developed a similar approach, which he expresses in shorthand as "blind variation and selective retention."
Thus, the philosophical stance that Popper and Campbell take is an interesting mix between realism and radical constructivism. Maturana (1988) took a similar stance to Popper and Campbell in his ontology of observing as expressed by the notion of "objectivity between parentheses", and explicitly rejected all epistemological stands that lead to solipsism. Popper, Campbell, Maturana and Varela all accept the existence of a real, physical world but argue that cognitively constructed claims or theories about that world can never be proven to be true or false. This places them in the radical constructivist camp. However, they also accept the existence of an external reality as an epistemic control over claims to know. Riegler (2001) and von Glaserfeld (1984, 1993, 1997, 2001) describe the radical constructivist stance; Niiniluoto (1999) compares his own and Popper's critical scientific realism against a wide range of other epistemologies. McKelvey (1999) reviews Cambell's and Popper's versions of scientific realism.
Here, it should be noted that Pattee reaches a similar understanding of knowledge from his biophysical approach:
Knowledge is potentially useful information about something. Information is commonly represented by symbols. Symbols stand for or are about what is represented. Knowledge may be about what we call reality, or it may be about other knowledge. It is the implementation of "standing for" and "about" - the process of executing the epistemic cut - that [we need] to explore. Heritable, communicable, or objective knowledge requires an epistemic cut to distinguish the knowledge from what the knowledge is about. By useful information or knowledge I mean information in the evolutionary sense of information for construction and control, measured or selected information, or information ultimately necessary for survival. [Pattee 1995a - my emphasis, his italics].
Although Pattee emphasizes the existence and importance of the epistemic cut between reality and the necessity of knowledge for survival, he did not account for the emergence of the cut. Popper provides the key insight to identify what Pattee missed.
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Ontological domains where knowledge can be found
To facilitate discussion of the emergence and evolutionary growth of knowledge, in Epistemology without a knowing subject (1968 - as republished in his 1972 book), Popper first introduced a metaphysical ontology of three domains or "worlds" within which various forms of knowledge could be categorized (Figure 4).
World 1 (abbreviated here as "W1") is the world of physics and chemistry, encompassing everything that exists, i.e., this is physical reality including the uninterpreted dynamics of complex systems.
World 2 ("W2") is the world of cybernetics and cognition that includes the embodiment of cognition and action and what Popper (1972) terms dispositional or subjective knowledge (i.e., knowledge embodied in the subject). In a physical sense, knowledge in W2 ("W2 knowledge") represents the situational propensities or "dispositions" embodied in the structure of a complex system that constrains the system to behave in certain ways in particular circumstances. In its simplest form, the cybernetic control structure of a system exhibiting feedback control is the basis for W2 knowledge. More complex forms of W2 knowledge may be represented in the structural associations and cyclical dynamics of macromolecules in a cell, or the strengthened interconnections of neurons in a brain that know the skills we have learned for better interacting with the world. Polanyi's (1958, 1966) 'tacit' or 'personal' knowledge is more-or-less synonymous with Popper's W2 knowledge.
Figure 4. Karl Popper's three worlds ontology (after Hall 2003).
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World 3 ("W3") is the world of the objective products of cognition, or of continued autopoietic self-maintenance in a changing environment, i.e., what Popper calls symbolically encoded or linguistically expressed knowledge.6 I disagree with Niiniluoto (1999: p. 23) who states that W3 is limited to the "products of human social action". I read Popper to say that W3 comprises the products of all kinds of cognition. Popper clearly defined W3 to include knowledge in the objective sense, which includes "the world of the logical contents of books, libraries, computer memories, and suchlike" (1972: p. 74) and "our theories, conjectures, guesses (and, if we like, the logical content of our genetic code)" (1972: p. 73), while the physical structure of the codified content remains always in W1.7 Pattee 1995a states:
The requirement for heritable or objective knowledge is the [epistemic] separation of the subject from the object, the description from the construction, the knower from the known. Hereditary information originated with life with the separation of description and construction.... Von Neumann ... states this epistemology of physical theory clearly: " . . . we must always divide the world into two parts, the one being the observed system, the other the observer. The boundary between the two is arbitrary to a very large extent . . . but this does not change the fact that the boundary must be put somewhere, if the method is not to proceed vacuously . . ." In physical theory, the observer is formally related to the observed system only by the results of measurements of the observables defined by the theory, but the formulation of the theory, the choice of observables, the construction of measuring devices, and the measurement process itself cannot be formalized.
...
The epistemology of physics would be relatively simple if this were all there were to it, but laws and initial conditions alone are not enough to make a complete physical theory that must include measurement. Measurement and control require a third category of knowledge called boundary conditions or constraints. These are initial conditions that can be compressed locally but that are neither invariant nor universal like laws. When such a constraint is viewed abstractly it is often called a rule; when it is viewed concretely it is often called a machine or hardware.
Both experience and logic teach us that initial conditions cannot be measured, nor boundary conditions constructed, with the deterministic precision of the formal dynamical laws. Consequently, this third category of knowledge requires statistical laws. Statistical laws introduce one of the great unresolved fundamental problems of epistemology. The dynamical laws of physics are all symmetric in time and therefore reversible, while statistical laws are irreversible. ...
Forms of evolutionary knowledge
Origins of embodied knowledge in W2
Prigogine, Kay, Schneider, Maturana, Varela, Pattee and Popper provide the phenomenological and epistemological framework for considering the emergence of knowledge-based complex systems. It now remains to explore specific conditions for the emergence of the necessary capabilities for self-control required for the existence of autonomous autopoietic systems.
From the prior discussion it should be clear that the key issue is to account for the origin and nature of the self-regulatory control information an autopoietic entity uses to maintain homeostasis of the system containing the control information. Given the extreme complexity and specificity of the apparatus required to replicate and assort hereditary information encoded in DNA molecules, and given that the phenomenon of autopoiesis must reasonably be assumed to have emerged from the
6 Urrestarazu (pers. comm.) would prefer to express this somewhat differently, to say that the term “objective” refers to the resulting structure of a material “product of cognition”. This structure may cause the enaction further cognition (problem solving ability) within a wider system if and only if it enters into a dynamical process that reproduces the kind of “continued autopoiesis self-maintenance in a changing environment” (i.e. knowledge reproduction) for the system in which it participates, independently of any observer. The “decoding” process is embodied by the overall structure of particular systems and may be completely inaccessible to an independent observer.
7 It should be noted that Maxwell (2002) in his otherwise quite favourable biography of Popper, disputes the ontological validity of Popper's three worlds. As is argued by Hoffmeyer and Emmeche (1991; Emmeche & Hoffmeyer 1991; Hoffmeyer 2002a), and as will be shown below, the biological evidence for the existence of three ontologically distinct domains as Popper has defined them is quite strong.
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near equilibrium of an unorganized chaos, following Rizzotti (1994) the first plausible autopoietic systems would have been very much less sophisticated.
To us the key feature not considered by Maturana and Varela for identifying an autopoietic system is that the system must maintain some its 'self' with some degree of functional integrity through a passage of time in the face of external perturbations. Survival through time implies that the homeostatic system must have some properties of its structural organization that provide negative feedback control to counteract perturbations that would otherwise lead to disintegration. The primordial autopoietic system would have coalesced close to equilibrium through a spontaneous emergence of simple structural mechanisms to transport and dissipate fluxes of exergy. However, to survive changing circumstances a nascent system must be so structured that at least some exergy is fed back into the system to maintain its integrity in the face of destabilizing perturbations and fluctuations in the medium or as environmental equilibria move away from those supporting the system's initial coalescence.
Assuming that the structure of the nascent system and its medium provide the possibilities, even though there is no mechanism to objectively codify and store control information, natural selection will begin to build survival 'knowledge' whenever/wherever systems persist long enough to begin accumulating a connected history. In the framework of Popper's 'general theory of evolution', it is a truism that those systems that disintegrate and return their components to the blind chaos of W1 do not build knowledge. However, where systems have by chance ("blind variation") coalesced into a structure that includes some homeostatic capacity that allows them to maintain their historical integrity in the face of perturbations, this structure embodies some W2 survival knowledge. Note that the concept of Embodiment of knowledge in an entity implies that it is diffusely present in the overall structural organization of the entity and not present as 'control information' in a discretely codified or even codifiable form. The control information is embodied int the instantaneous dynamic structure.
Even if partially autocatalytic systems later disintegrate to return their components to the environment, systems that successfully produce more of the same kinds of components that are involved in their structure will make it easier for other autocatalytic systems using those components to emerge from that environment. This might be considered a form of environmental knowledge (where knowledge is defined as ‘solutions to the problems of life’). The stage between Turbulence and Coalescence in Error: Reference source not found illustrates this stage.
Thus, even the survival over limited time of homeostatic systems having some autocatalytic capability to produce suitable components may work to prepare the environmental medium to more readily form such systems. It is reasonable to believe that in this epoch, the W1 environment will itself develop in ways that shift the equilibrium between integration and dis-integration of components so that the integrated systems do not so readily fall apart. It follows that coalescent entities with favorable structures will 'live' for increasingly long stretches of time, until lineages are formed that do not dis-integrate. These establish continuous historical heritages. Survival 'knowledge' accumulated in an autopoietic entity is lost if it dis-integrates. Survival knowledge continues to accumulate in a lineage as long as the lineage survives in an organized state with an unbroken history (i.e., heritage). In Error: Reference source not found, this is ‘stabilized autopoiesis’.
To this point, the discussion has not considered reproduction. Although the first of the barely stabilized autopoietic systems might survive for a while, given the range of perturbations that can arise in a chaotic environment, they probably don't embody enough organizational knowledge to survive for long.
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Dis-integration I ntegration
Tentative solutions
Stable solutions
Selected solutions
Turbulence
Coalescence / Emergence
Dispositional autopoiesis
Stabilised autopoiesis
Semiotic autopoiesis
†
Knowledge sharing
Sharedsolutions
†Criticised solutions
Evolutionary Stage
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Dis-integration I ntegration
Tentative solutions
Stable solutions
Selected solutions
Turbulence
Coalescence / Emergence
Dispositional autopoiesis
Stabilised autopoiesis
Semiotic autopoiesis
††
Knowledge sharing
Sharedsolutions
†Criticised solutions
Evolutionary Stage
††
††
Figure 5. Stages in the evolution of autopoietic knowledge.
However, with historical continuity, 'reproduction' begins to play a role. In its simplest form (i.e., requiring the least knowledge beyond chaos), reproduction would probably have involved nothing more than growing larger by incorporating additional components in favorable ratios and structural locations until the assemblage becomes physically unstable and fragments into pieces. If at least some of the fragments retained enough of the favorable structural organization to maintain an autopoietic existence, those histories would be preserved and added to. Even this nearly chaotic form of replication would serve to multiply the history of solutions that worked. It becomes quite appropriate then to talk about the currently surviving entities as 'spearheads' (Popper 1972:243) inheriting dispositional knowledge embodying in their structures solutions to the problems of life (i.e., 'survival knowledge' or control information) replicated from their linear ancestors.
Van Duijn et al. (2005) present the case of the bacterium E. coli, where the structural organization provides a minimal form of cognition to actively seek 'food' and avoid danger (see also Lyon 2004). The existing structural organization of the bacterium includes receptor molecules in the cell membrane called MCPs that respond to the concentrations of a wide range of environmental chemicals, a phosphotransferase pathway, bistable motors that can rotate in either direction (i.e., counter clockwise - 'CCW', or clockwise - 'CW') to drive flagella, plus a 'switch' protein associated with the motor that increases the probability that the motor will switch to CW mode. In CCW mode the flagella rotate in synchrony to propel the bacterium in a linear fashion. In CW mode, rotation is asynchronous and causes the cell to tumble randomly. A second pathway adapts to long-term changes in concentration so that short-term changes in the concentration of attractive or repellant chemicals can be detected and responded to. The net effect is that a short-term rise in the concentration of repellants or decrease in attractors causes the bacterium to tumble and reorient in a random direction. On the other hand, if environmental attractors rise and repellants fall, unidirectional movement will continue for some time. Thus, the net directional movement will be up the gradient of attractors and down the gradient of repellants. The 'knowledge' that attractors
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equate to metabolically useful 'food' chemicals and repellants equate to 'danger', has been built into the structure of the bacterium by selection. In E. coli, that structure is specified to a large degree by a genetic code existing in the DNA chromosome of the cell, such that particular kinds of proteins are synthesized that work this way.
Obviously with no genetic system to retain and reproduce control information in any objective form, the propagation of survival knowledge would be subject to chaotic variation and it is likely that fragmentation would perturb many incipient lineages to the extent that they dis-integrate and lose their accumulated history. However, as long as some lineages survive, simply by surviving, those that do will continue to accumulate more and more survival knowledge (Popper’s general theory of natural selection and Campbell's blind variation and selective retention).
In the early days of this process when autopoietic systems do not survive for long, disintegrating systems will return their once functional components to the medium, thus maintaining favorable conditions for the coalescence, emergence and growth of other autopoietic systems. However, when systems with longer and more successful histories and reproductive abilities begin to accumulate in the environment, the more successful survivors will compete for and sequester suitable functional components and consume exergy resources to fuel their continued growth and multiplication to eventually destroy the close to equilibrium situation that made the initial emergence of autopoiesis possible. This creates selection to use available resources of components and exergy more efficiently, and to synthesize required components from simpler/lower value starting materials. Eventually, environmental conditions will no longer favor the coalescence of new lineages and the survivors will thus move farther away from equilibrium. In Error: Reference source not found, this represents the stage of dispositional autopoiesis – referring to Popper’s (1972) concept of W2 knowledge embodied in the structural "disposition" of organisms. Bentolila (2005) calls this "live memory".
Codification to preserve knowledge in W3
To this point, I have discussed the origins of autopoiesis only in the most general terms. However, laboratory work suggests that complex organic polymers will form in the prebiotic chemistry of an aqueous reducing environment containing compounds based on C, H, O, N, P, S, etc. that subjected to almost any kind of excitation energy sufficient to activate simple carbon based molecules to the point that they can relax by bonding with other molecules, or heat flux situations that favor polymerization through dehydration reactions. Amino acids polymerize into protenoids that can hydrophylicaly form micelles when rehydrated. Some randomly formed protenoids have shown at least mild catalytic activity and excitibility (Fox 1980, 1991, Fox et al. 1994; Andras & Andras 2005). Lipids can group together form bilayered vesicles, where hydrophilic radicals face either the interior space of the vesicle or the environment (Cavalier-Smith 2002; Del Guidice & Preparata 1995; Rizzotti 1994; Segré & Lancet 2005). Nucleotides with energy rich phosphate groups can transfer activation energy held in the phosphate group to other molecules in ways that may activate them to polymerize; or, through loss of active phosphate groups or even simple physical dehydration (e.g., Smith et al. 1967, Kazakov et al. 2006), they can polymerize themselves to form long nucleic acid polymers (Woese 1967; Crick 1968; Orgle 1968; Hughes et al. 2004; Muller 2006). None of these chemicals do much on their own, but a mixture of the various polymers, monomers and substrate materials, when subjected to the organizing forces of a flux from source to sink, may coalesce where conditions are particularly favorable to form incipiently autopoietic organizations.
Undoubtedly, one of the problems on life in lineages whose only form of historical knowledge is embodied in the three dimensional dynamics of their structure, is to retain through time their successful solutions with some degree of fidelity, especially through the process of reproductive
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fragmentation (Bentolila 2005). Clearly any system capabilities that serve to protect aspects of proven solutions by codification and packaging would have selective value by comparison to the chaotic reproduction of diffuse structural knowledge through passive fragmentation. Based on evidence for heterocatalytic (i.e., enzymatic) as well as autocatalytic properties of nucleic acid polymers, it is reasonable to suppose these macromolecules may have played cybernetic control functions in early autopoietic systems. This would facilitate the evolution of a system to codify control information by establishing an epistemic cut. By taking advantage of the self replicating capabilities of the nucleic acid polymers, an autopoietic system replicating these molecules, would also be replicating the structural or enzymatic functions of those molecules performed in the autopoietic system (Hughes et al. 2004). In today's systems DNA appears to have no direct roles in active functions. RNAs still serve both as code carriers (in transfer RNA) and structural/catalytic roles (in protein synthesis).
Once any structural knowledge or control information relating to the autopoietic system as a whole is able to be represented in the structures of macromolecules that are themselves autocatalytic, the obvious value of the self-preservative capacity of autocatalysis can be shaped and improved through further stabilization of lineages carrying such macromolecules. This represents the first population of Popper's W3 with persistent and shareable survival knowledge. The value of protecting the tested knowledge in such stable and self-replicating molecules sets the stage for evolution of the kinds of DNA and RNA-based epistemic systems we now know as Genetic systems. Pattee has discussed at length stages in the refinement of replication, transcription and translation systems for the semiotic preservation and application of knowledge.
In this discussion it should be noted that this supposed evolutionary path offers no means to translate embodied experience of life back into the DNA code. There is no evidence that such a system exists even today. As discussed by Kauffman (1993), knowledge of life has been built into DNA codes solely through the process of blind variation and death of lineages carrying code variants that disrupted or reduced survival of those lineages. As Popper argued quite effectively, what is left will in general encode a broader, deeper and overall more effective response to the problems of persisting in the real world.
Early life must have still been quite fragile by comparison to the kinds of robustly self-maintaining cellular organisms we know today. Dis-integration would have been a common phenomenon, scattering tested components into the environment - including usefully coded nucleic acid sequences that would then be available for incorporation into other living entities. Even today many bacteria retain the capacity to share and incorporate exogenous DNA into their functional genomes by processes of transduction and transformation (Avery et al. 1944). Thus, I would argue that at least in the early stages of the evolution of life after the emergence of a codification system, all living things shared a common pool of hereditary knowledge, more or less in every possible combination. In Error: Reference source not found, this represents the stage of semiotic autopoiesis. Through this point in the evolution of life, it is very likely that survival knowledge is shared promiscuously via fissions and fusions and disintegration and coalescence of autopoietic patches in the overall dissipative media.
However, it is likely that some combinations of genes would work better together to stabilize and grow in some autopoietic patches than would other combinations in other patches. There would be advantages to lineages possessing such combinations if the different genes were physically linked together in self-reproducing packages (i.e., Chromosomes encoding compatible bits of control information in its genes).
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Two worlds of organismic knowledge or "code duality"
Hoffmeyer and Emmeche (1991; Emmeche & Hoffmeyer 1991; Hoffmeyer 2002a) have also considered the evolutionary origins of the self-referential capability to apply control information as required for autopoiesis and life, and end up with an evolutionary epistemology they call Code duality that is similar to Popper's. I quote these sources at length, because they cover the same ground with a somewhat different viewpoint from ours. Beginning with Hoffmeyer and Emmeche (1991):
[W]hat is the basis of this self-reference, and thus the basis of life? We shall suggest here that the central feature of living systems allowing for self-reference, and thus the ability to select and respond to differences in their surroundings, is code-duality, i.e. the ability of a system to represent itself in two different codes, one digital and one analog (Hoffmeyer 1987)....
In this discussion, I equate Hoffmeyer and Emmeche's "analog" code to situational knowledge in Popper's W2 for reasons argued below.
Self-reference clearly depends on some kind of redescription. The system must be able to construct a description of itself (Pattee 1972, 1977) [in Popper's W3]. This description furthermore must stay inactive in - or at least protected from - the life-process of the system, or else the description will change - and ultimately die with the system. In other words, the function of this description is to assure the identity of the system through time: The memory of the system. In all known living systems this description is made in the digital code of DNA (or RNA) and is eventually contributed to the germ cells.
.......
[The] need for the participation of cellular structure shows us that a sort of 'tacit knowledge' is [also] present in the... cell (Polanyi 1958, Pattee 1977) [in Popper's W2]. And the existence of this tacit knowledge hidden in the cellular organization must be presupposed in the DNA-description. Thus, the digital redescription is far from a total description.
The realization in space and time of the structural relations specified in the [nucleic acid] digital code defines what kind of differences in the surroundings the system will actually select and respond to. Through this realization a new phase is initiated, the phase of active life. One might say that in this phase, the 'analog phase', the message of the memory is expressed.
Hoffmeyer 2001a states:
... I have suggested the term Code-Duality to describe the semiotic dynamics of life: Organismic and cellular function is very much dependent on surface properties, shapes and topological ordering of macromolecules in relation to the subcellular architecture of membranes which extend throughout the cellular body. Subcellular architecture is itself molded by evolutionary processes and thus represents successful responses to cellular, bodily, or environmental challenges of the past which are most often also challenges of the present and very probably of the future. [i.e., corresponding to Popper's (1972) "solutions to problems".]
But these representations are not sequential or digital. Rather they are analog codes for particular events and situations. The stereochemistry of a receptor molecule on the surface of a cell may for instance be constrained so that the receptor will recognize and bind only a certain kind of hormone molecule, say adrenaline, and no other. Thus the receptor is an analog code for adrenaline - in this case created very early in evolution and fine-tuned in its fit through hundreds of millions of generations.
....
Suppose that eventually a living system arose from the primordial soup—or wherever it was. Then we will have to ask: Who was the subject to whom the differences worked on by such a system should make a difference? If one admits at all, that living systems are information processing entities, then the only possible answer to this question is: the system itself is the subject. Therefore a living system must 'exist' for itself, and in this sense it is more than an imaginary invention of ours: For a system to be living, it must create itself, i.e. it must contain the distinctions necessary for its own identification as a system. Self-reference is the fundament on which life evolves, the most basal requirement. (This does not pertain to non-living systems: There is no reason for the hydrological cycle to know itself. Thus, rivers run downstream due to gravity, water evaporates due to the solar heat, nowhere does the system depend on self-recognition)....
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Hoffmeyer 2002a
A... major precursor for the idea of code-duality was the American biophysicist Howard Pattee's distinction between a ‘linguistic’ and a ‘dynamic’ mode of complex systems (Pattee, 1977). Pattee explicitly refers as a source for this idea to Niels Bohr's discussion of the complementarity principle as pertaining to the phenomenon of life and also to the work of John von Neumann. In a recent paper Pattee quotes von Neumann saying:
We must always divide the world into two parts, the one being the observed system, the other the observer . . . . That this boundary can be pushed arbitrarily deeply into the interior of the body of the actual observer is the content of the principle of the psycho-physical parallelism—but this does not change the fact that in each method of description the boundary must be put somewhere, if the method is not to proceed vacuously. (von Neumann (1955), quoted in Pattee, 1997). [Compare this to Maturana's (1970) concept of the observer.]
Pattee now explains von Neumann’s point in the following way:
... [T]he function of measurement cannot be achieved by a fundamental dynamical description of the measuring device, even though such a law-based description may be completely detailed and entirely correct. In other words, we can say correctly that a measuring device exists as nothing but a physical system, but to function as a measuring device it requires an observer's simplified description that is not derivable from the physical description. The observer must in effect choose what aspects of the physical system to ignore and invent those aspects that must be heeded. This selection process is a decision of the observer or organism and cannot be derived from the laws (Pattee, 1997).
Since not only human beings but living systems at large are fundamentally engaged in observations or measuring processes it follows that: "we must define an epistemic cut separating the world from the organism or observer. In other words, wherever it is applied, the concept of semantic information requires the separation of the knower and the known. Semantic information, by definition, is about something" (ibid). And thus according to Pattee in all living systems we must have one part of the system operating in a linguistic and time-independent mode (i.e. the DNA [in W3]) and one part operating in a dynamic and time dependent mode (i.e. the protein system) [i.e., in W2].
Pattee underlines that he is not suggesting a Cartesian dualism here but only a ‘descriptive dualism,’ for although a measuring process depends on choices which cannot be derived from laws, such choices are seen by Pattee as functions coded in DNA and ultimately generated by natural selection.
But this appeal to natural selection as the mechanism for bridging the Cartesian dichotomy between knower and known is not convincing. How could a purely mechanical process like natural selection possibly push non-knowing dynamical systems across the logical gap separating such systems from the realm of measurement and knowledge? Many people apparently entertain this illusion of natural selection as a mysterious bridge across the Cartesian Divide. But natural selection is either a selection in the true sense of this term in which case a selector (and thus measurement) must be presupposed for its working so that some kind of preference (the essence of selection) can be executed, or it is not a true selective process: in which case it cannot possibly explain how preferences can possibly arise in the midst of the physical world.
Like Bohr and later von Neumann, Pattee has taken a long and courageous step in facing that borderline paradox which necessarily must appear, whenever you subscribe to an ontology of natural law. By this expression I try to characterize the conception of the world, which Pattee formulates quite unambiguously..., where he says that ‘these [physical] laws describe all possible behaviors.’ The transfer of Bohr's thinking about complementarity to the realm of life processes doesn't seem to help much here. For if complementarity is thought of in ontological terms we are immediately brought back to the dualism Pattee explicitly rejected, but if complementarity is thought of in epistemological terms the claim for complementarity is reduced to the assertion that even though we cannot describe the semiotic dimension of the world in the same language we use to describe the dynamic aspects of the world, this is due to a deficiency of language or thought. The semiotic dimension of life is like glimmerings which we cannot reach behind, because we are totally enveloped by them.
...
Code-duality transgresses the Neumann-Pattee thesis by claiming that the linguistic or symbolic mode and the dynamic mode are both fundamentally semiotic modes. The distinction does not separate a semiotic mode from a non-semiotic or dynamic mode but rather posits two different kinds of semiotic coding. Thus semiotic processes characteristic of the ‘linguistic mode’ are based on digitally coded symbols, while the semiotic processes characterizing the dynamic mode are indexical or iconic and analogically coded. The analogically coded signs thus correspond to the myriads of topologically organized indexical and iconic semiotic processes in cells and organisms which incessantly coordinate body parts and their relation to environment and in so doing an analogically coded sign also is responsible for the interpretation and execution of the genomic instructions.
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To me, the application of Popper's evolutionary epistemology and three worlds ontology accounts for the two kinds of epistemic cuts involved in the origins and evolution of knowledge. The evolutionary assembly of a cybernetic system as a consequence of blind variation and selective elimination/retention builds structures and dynamic connections that work in ways that tend to self-maintain the dynamic state of the system. This is a state of being organized in W1 in such a way that the structural components are able to maintain a certain degree of self-regulated control over the flux of energy through the portion of the environmental medium where they exist, and not in any of the countless other ways the same structural components could be distributed that would be at the passive mercy of their environments.
I would not call this an analog code, but rather an organizational assembly of components that creates a kind of attractor basin keeping their mutual interactions within some kinds of bounds. However, it can still be argued that there is some kind of epistemic cut between the otherwise random collection of components versus the structural or dispositional knowledge represented in the fact that the structure has a particular dynamic state of autopoiesis that has as its 'purpose' the continuation of that state. The control information required for regulation exists in (and only in) the direct physical relationships and dynamics of the interacting components. In Popper's epistemology this is selected knowledge belonging to W2, but to call this kind of analog information a code confuses the issue.
The concept of a code is that it can abstractly describe the state of a system in a more compact way than a complete specification of the system itself. Where structural knowledge is concerned, the knowledge is in the conformation of the structure itself. Only when the source of the control information is physically separated from active components of the system in a compressed, abstracted and energetically degenerate and inactive structure, such as the sequence of nucleotides in a DNA chromosome (i.e., as described by Pattee), does the information/knowledge become codified and begin to form Popper's W3. There is then a second cut between the codified control information (control codes) and the control structure, while the first cut, between the physical control structure and the dynamic activities being controlled still exists.
The origin and evolution of genetic systems to manage cellular knowledge
In today's epoch, all living entities maintain their codified (i.e., W3 - as differentiated from structural or W2) survival knowledge in the sequences of nucleotide monomers in nucleic acid polymers called chromosomes. As Kauffman (1993) discusses at some length, although the blind introduction of new control information can stabilize, change or even add new attractor basins for the organized system, new information probably more often tips the organizational dynamics of the system out of an attractor basin onto a trajectory that leads to chaos and disintegration. There will be obvious advantages to lineages possessing means to isolate code sequences tested through survival in the lineage from exogenous codes by maintaining these codes behind barriers that keep out foreign DNA and/or to evolve systems that degrade DNA strands taken up from the environment before any information they carry is translated or recombined with inherited chromosomes. Both strategies are well known in living organisms today.
Once barriers evolve to cut off the existing survivors of an embodied lineage from the promiscuous exchange of codified control information, different kinds of trophic specialization can begin to evolve as distinct Clonal species. Hall (1966) discusses some likely circumstances and selection pressures leading to the differentiation prokaryotic and eukaryotic organisms as distinct types of trophic specialization emerge from the era when life was physically or genetically promiscuous8.
8 Note there are important differences between Hall's approach and Margulies's (Sagan 1967; Margulies 1968, 1970).
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However, there is a downside to genetic isolation. Isolated individuals of a clone no longer have access to share in a wide range of experientially tested knowledge from other, related individuals, and evolution of the isolated lineage is limited to the slow pace of change in single lineages. Thus, I would expect the evolution of a number of strategies to allow the continued exchange of genetic information between closely related lineages (i.e., those sharing many genes in common due to a comparatively recent common ancestry, and thus unlikely to be disrupted by exogenous control information).
One strategy for identifying whether an exogenous piece of naked chromosome taken up from the environment might be useful is to test whether it has a sequence of code matching that in the host cell (i.e., because it came originally from a related individual. In this case, some or all of the exogenous DNA may be spliced into the cell's chromosome, replacing the existing - more or less matching segment. This is known as Transformation, and was used by Avery, McLeod and McCarthy (1944) to prove that DNA rather than protein was the carrier of hereditary information.
A second, more sophisticated strategy, would be to package or wrap chromosomal control information in the same kind of material that members of the clone use to bound their autopoietic spaces from the external environment. Presumably this genetic package would then be recognized as belonging to a self sharing a common ancestry, and thus be safe to assimilate. More sophisticated transfer mechanisms might encode specific molecules to recognize and bind to clonal members. Today's viruses depend on both of these strategies to inject codified nucleic acids into 'host' cells. Although in many cases the transfer mechanism has been subverted simply to make more virus (often killing the host cell in the process), viral transfer, known as Transduction, discovered by Zinder and Lederberg (1952), is still an important mechanism for the lateral transfer of tested information between related lineages - although, in many cases infecting virus cause the cells they invade to disintegrate.
A third, still more sophisticated form of genetic exchange between bacteria, involving direct physical contact between cells, known as Conjugation, discovered by Lederberg & Tatum (1946). In the known cases, the entire process seems to be driven by the donor cell, which carries a specialized chromosome known as a plasmid that control its own transfer. Plasmids may also include genes from the donor cell's primary chromosome. One can speculate that this might be a more evolved case of what was originally a viral transduction process.
It should be noted (1) that all of these bacterial processes involve established subsystems in the cell lines for splicing and recombining sequences of DNA between different chromosomes, and (2) that none of these mechanisms are directly involved in cellular reproduction. However, such recombination mechanisms known in the bacteria are evolutionarily highly important (as shown by the speed with which drug resistance genes can be passed between different strains of bacteria) in sharing and recombining tested solutions to the problems of life across lineages that otherwise reproduce clonally.
Hall ([1966]) discusseed circumstances likely to be involved in the origin and early evolution of eukaryotic cells. To date there is no new evidence to invalidate the schema presented there. Hall argued that two major adaptive responses were open to organisms to compensate for the increasing degradation of resources in the environmental once the existing supplies of components and energy fluxes were fully exploited and genetic isolation was evolved. These would constrain the evolution of the genetic systems to manage the control information in quite different directions.
1. The evolution of increasingly complex metabolic pathways able to exploit chemical and solar exergy directly together with secondary metabolic and biosynthetic capabilities able to assemble necessary substrates and monomers from simpler starting materials - i.e., the autotrophic
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Producers in the complexifying ecosystem. The complexity of the necessary electron transfer and other 'molecular handshaking' activities would seem to establish a requirement for a comparatively rigid boundary and membrane system able to maintain the stereochemical structure of the necessary molecular machinery. On the other hand this would seem to impose few constraints on the genetic system beyond the collection of genes into a single linkage group to ensure that daughter cells both receive a full copy of the codified knowledge (this ignores the interesting biology associated with plasmid chromosomes). This seems to involve no more than attaching the chromosome to a point on the cell membrane, such that when the chromosome is replicated as the membrane also grows, the attachment points and the copied chromosomes each end up in the separate daughter cells. This pathway led to the evolution of today's Prokaryotes.
2. The evolution of motility mechanisms to enable the organism to move around on surfaces in the environment to sop up widely distributed patches of primordial 'food' or even whole organisms that had captured energy and synthesized food - i.e., the heterotrophic Consumers.. In terms of the evolutionary requirements for new information, I believe that the motility option is substantially the simpler, in that it only requires the development of cytoplasmic motility based a few molecules able to change their shapes in response to imposed chemical or physical gradients such as represented in today's amoebas (i.e., a simple kind of 'measurement' system in Pattee's terminology). However, this lifestyle would place significant constraints on the evolution of the genetic system, where mechanisms that favored protection of chromosomes from cytoplasmic shearing forces. Solutions to minimize damage from cytoplasmic shearing include partitioning the genetic code into several shorter chromosomes - each with a different part of the code, coiling and binding the naked DNA with proteins to strengthen and further reduce the overall length of the chromosomal packages to something on the order of cellular dimensions, and compartmentalizing the cytoplasm containing the DNA behind a second set of cytoplasmic membranes to completely separate the hereditary apparatus from the motile cytoplasm. This strategy led to the evolution of cells with nuclei, known as Eukaryotes.
Packaging of the coding sequences in the DNA chromosomes in a protein matrix, partitioning the code into several chromosomes of shorter lengths, and compartmentalizing the hereditary apparatus within a second set of (nuclear) membranes would have made it much more difficult for such cells to share tested genetic codes with other related lineages. The advantages to retaining such sharing capacities would powerfully constrain the further evolution of the eukaryote genetic system. Some amoeboid types of organisms appear to have partially solved the problem by becoming multinucleate, which would give several independent threads of heredity in the same cell. There is also some evidence that some means for horizontal gene transfer (e.g., viral transduction) still provides for the slow exchange of hereditary information between more distantly related lineages. The confusion over the early evolutionary derivation of prokaryotes and eukaryotes suggests that horizontal gene transfer must have remained fairly common even after lineages began to differentiate (Embley & Martin 2006; Ciccarelli et al. 2006).
More effectively, the fusion (conjugation) of separate cells to form a single cytoplasm would serve to bring two nuclei with their separate heredities together in a single cytoplasm. What remains is some mechanism to fuse or break down the nuclei such that chromosomes from the different sources can be brought together to exchange genetic information. In present day systems, the mechanism of cell fusion requires a precise matching of receptors and substrates to occur to ensure that only proper partners fuse, which is then followed by a chromosomal choreography that pairs and recombines genetically similar codes at the level of the DNA molecule in ways that resemble those in prokaryote recombination. Cell fusion leaves the combined cell with a double set of hereditary information, which is followed by another complex choreography of two cell divisions and one chromosome replication, assisted by specialized cytoplasmic motility mechanisms to sort one complete set of the hereditary knowledge into four daughter cells. Single celled organisms
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show a range of variations on this theme. This is what we know as Sexual recombination and assortment. Except for the necessity to return the ratio of the genome to the rest of the cell to what it was prior to the conjugation event that brought the two sets of chromosomes together, sexual recombination does not involve reproduction. The actual reproduction of unicellular organisms is normally asexual or clonal.
However, due to the consequence of the regular sharing of hereditary information across otherwise clonal lineages, the lineages that are periodically mixing and sharing their genetic experience come to share a common gene pool and can be considered to be Biological species, separated from other biological species by Barriers to gene flow. Once separated, the different species can evolve independently as evolutionary entities in their own rights (Gould 2002).
Orders of Autopoiesis
Is There More Than One Order of Autopoiesis?
As argued early in this paper, complex dynamics may emerge at many different levels of organization in a dissipative system conducting energy from a source to a sink. Thus, it is reasonable to ask whether the complex dynamics at different levels in the global system can themselves become autopoietic. I have already shown that systems based on macromolecules can evolve enough complexity at the 'cellular' level of organization to become autopoietic. These are termed first order systems.
Maturana (2002), Mingers (2003), R. Kay (2001) and Urrestarazu (2004) and several others have argued that autopoiesis as defined by Varela et al (1974) only properly applies to the cellular level of organization. Hall (2003; 2005; Hall et al. 2005) argues that autopoietic entities may also exist at higher levels of organization.
It remains to see if complex dynamics can emerge at higher levels of organization involving autopoietic cells as components that would reasonably be considered to be autopoietic, and to see what roles autopoietic cognition and knowledge would play in their subsequent evolution.
First Order Autopoiesis: Prokaryotes and endosymbiotic assemblages
Hall ([1966]) and Margulis (Sagan 1967; Margulis 1968, 1970) cited mounting evidence that chloroplasts and mitochondria:
1. had their own DNA that was replicated and transcribed independently from cellular DNA,
2. always formed and were multiplied through division of previous organelles, and
3. respectively exhibited many structural similarities with free living blue-green algae or bacteria.
They inferred from the evidence that these organelles represented independent lines of evolution that had subsequently formed an endosymbiotic association with eukaryotic ancestors lacking capabilities for photosynthesis or oxidative metabolism. Supporting this argument is the fact that the enzymes involved in the Krebs cycle for fermentive metabolism are soluble and dispersed throughout the cytoplasm. The molecular apparatus required for photosynthesis or oxidative metabolism is respectively tied to the internal membranes of chloroplasts and mitochondria respectively. Hall ([1966]) also noted that similar kinds of endosymbiosis (where there are free-living close relatives) had evolved many times in single celled organisms. In some algae (for example), there have been cases of endosymbiosis taking place sequentially in the same lineage
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(Patron et al. 2006), where cells are built like Russian dolls, with two or three layers of eukaryotic membranes each containing an nucleus and surrounding another set of cellular components contained within their own membrane.
Whatever the precise pathway of events, endosymbiosis represents the fusion into a single autopoietic entity (the eukaryote cell) of separate autopoietic entities that previously held independent existences. At least initially, the host and endosymbiont would have maintained cognitively separate existences to achieve their own ends in the cooperative enterprise of life, as is the case today with photosynthetic algae living in coral polyps, where either type of entity can live on its own in favorable circumstances. In this sense the endosymbiont represents a level or order of complexity above that of simpler free living ancestors.
However, as the symbiotic association persists through time, and the partners evolve to work more effectively together, the association becomes obligatory and the joint entities evolve more and more as a single biological species with different kinds of organelles, such that the activities of the original symbiotic ancestors are no longer distinguishable as an autonomously defined level of organization. Because obligatory endosymbionts are protected within the cytoplasm of the host cell, they are presumably cut off from ready gene exchanges with relatives in other lineages or that may still be free living. Based on observations of today's chloroplasts and mitochondria, and many obligatory endoparasites, it appears that there evolutionary advantages may be gained from actually transferring the codes for 'endobiont' genes to the nuclear genome of the host cell where they have access to recombination and assortment using the host cells apparatus for sexual recombination. However, the resulting compound entity, though more complex than its various free-living ancestors taken independently, still exists as a first order (i.e., cellular) autopoietic entity.
Second Order Autopoiesis: Multicellular Organisms
Mulitecllular organisms are certainly living, but are they autopoietic and do they represent a higher order of autopoiesis than single cells?
To briefly summarize an argument that will be developed in more detail elsewhere, I argue that multicellular organisms represent a second order of autopoiesis.
1. Many, if not all of the cells comprising a multicellular organism are themselves autopoietic, as can readily be proven by isolating single cells into appropriate culture media, where they will continue living, and in many cases even continue growing and dividing.
2. When the focus of analysis is set at the level of the multicellular organism, individual cells are the component subsystems and the environment external to the organism's integument is the external environment or supersystem. The following complex system dynamics can be observed, fulfilling the requirements for the system to be considered to be autopoietic:
a. Self-identifiably bounded (demarcated from the environment by membranes, or the entity's components are identifiably tagged): In most cases there is a visible epidermis, cuticle, or other self-produced boundary composed of or manufactured by cells working together under the embodiment of a common developmental program.
b. Individually identifiable components within the boundary (complex). Composed of individually discrete cells. Even for some of the minor phyla where all or part of the adult is formed of a multinucleate cytoplasmic syncytium, the embryonic development of the organism is based on the multiplication and differentiation of cells before the internal cell membranes are absorbed.
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c. Mechanistic (i.e., a system driven by cybernetically regulated exergy fluxes or metabolic processes). Activities of the multicellular entity are driven by molecular metabolism as controlled by the dissipatively dynamic activities of a cellular neuro-endocrine system coordinating cells in the operation of musculoskeletal system, and the distribution of metabolically essential molecules.
d. System boundaries internally determined (self referential). See part a. above. The system boundaries are developmentally organized under direction of embryonic developmental processes regulated by the entity's hereditary knowledge.
e. System intrinsically produces own components (self production). See previous answer.f. Self-produced components are necessary and sufficient to produce the system (autonomy). All
cells in the organism come from the division, growth and differentiation of preexisting cells formed within the developmental framework of the organism. The only counter argument is that most multicellular organisms trace their existence to a single fertilized egg cell, although in some cases there are asexual means of reproduction that involve various kinds of fissioning or budding of multicellular offspring from the multicellular parent.
3. 'Lower' multicellular organisms carry W3 knowledge in their DNA chromosomes that is devoted to regulating the intercellular dynamic interactions of cells with other cells in the organism - and is thus an evolved product of the organismic level of complexity. The fact that each cell has its own set of chromosomal DNA is mitigated by fact that in the normal situation all cells in the organism trace their ancestry to the fertilized egg and thus are all so to speak working from the same codebook. The W2 knowledge embodied in the fertilized egg or other propagule provides the necessary framework to translate the DNA code into embodied structure.
4. 'higher' multicellular organisms have well developed cognitive capacities for selective learning, which in a very few cases is supplemented by a capacity for extrasomatic transmission of 'cultural' knowledge from parent to offspring that exists as further evidence for a level of coordinating knowledge that is only relevant to the organizational level. Such transmission is mediated by pheromones, imitation, and eventually language and the products of language.
Third Order Autopoiesis: Colonies, Societies and Organizations
Colonial organisms
Several classes of organisms have evolved colonial forms of structural organization. These include lineages that alternate sexual and asexual reproduction or that have facultative or obligatory modes of asexual reproduction. The animal cases are more easily analyzed. In most cases these are found in lineages where the ancestral body plan is that of a polyp that reproduces by budding, where the new polyps remain connected to form some kind of super-organism. Where all the polyps are of the same type these are really no more than a collection of genetically identical entities that happen to remain connected for the exchange of nutrients and perhaps warning signals via a nerve net or chemicals circulating through the intercellular medium. However, there are also a number of cases, such as Portuguese Men of War, sea pansies, various kinds of bryozoa (ectprocts) and tunicates (sea squirts) where polyps become developmentally specialized to perform quit different tasks for the overall colonial structure, e.g., defense, food capture, digestion, and reproduction. As noted by Wilson (1975), the polyps develop sequentially from a single larva. In one sense, this might be a similar situation to what led to the development of segmental development in a variety of different animal groups. Again, all share in the common genome due to asexual reproduction, but boundaries between the individual polyps may become quite indeterminate as far as the overall colonial organism is concerned. Here, I am inclined to treat this as a developmental process of a single organism, and thus not representing a significantly higher level of complexity.
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Wilson (1975) lists the following advantages deriving from the colonial type of organization in marine organisms:
Resistance to physical stress for shallow water forms where organisms are subject to wave action and sedimentation. The colonial form raises individuals away from the bottom and enables them to create more effective feeding currents overall.
Liberation of otherwise sessile forms for a free-swimming, pelagic existence. This has been achieved by some kinds of polypoid coelenterates and urochordates (sea squirts).
Superior colonizing and competitive abilities. Defense against predators.
However, setting the level of analysis to that of the colony does not yield a clear result. Although the colony as a whole is clearly living and thus autopoietic, and in the complex cases clearly have modes of life that differ from individual founding polyps, given the lack of identifiable physical or genetic individuality of the constituent polyps, it is arguable as to whether such colonial organisms should be considered to be a higher order of autopoiesis different from that of a common multicellular organism.
The plant world offers similar situations to the colonial animals that simply form many polyps of the same type. Where plant examples become more problematic is with the formation of alliances and complex symbioses, such as the fungal rhyzosphere forming in conjunction with some trees that allow the collective organism to survive and compete in areas where species involved in the association could not persist on their own. However, the interesting interactions occur in the soil where they are essentially invisible to science. Consequently, we know too little about the dynamics of such associations to analyze them in any detail.
Social organisms - the evolution of 'social homeostasis'
The cases of social organisms such as ants, bees, termites and possibly even mole-rats are more easily analyzed. In this case the colony in the hive, anthill or termite mound establishes the level of focus. In the eusocial hymenoptera (ants and bees) a fertilized diploid queen carrying a lifetime supply of sperm founds a colony, and begins laying eggs. Fertilized eggs are diploid and develop into females; unfertilized eggs develop into haploid males. Depending on how the diploid female larvae are fed, their sexual development is suppressed and they develop into sterile workers who help to maintain and feed the growing population of the colony, or they develop into future queens. In most social bees there is only one kind of worker but these will carry out a range of specialized tasks as they age, whereas in some ant species, larvae differentiate into a variety of morphologically different kind of workers that perform specialized jobs for the colony.
Colonial honeybees reproduces in three ways (Wilson 1971). When the colony grows to a critical size, workers begin building special enlarged cells where the larvae will be fed in ways that cause them to differentiate into new queens. A larger number of cells are set aside in which the queen lays haploid eggs that develop into male drones. Before the first of these new queens eclose from the pupal stage, the original queen is expelled from the hive by workers, and will depart with a significant fraction of the existing workers to found a new hive. The first of the new virgin queens will attempt to kill or drive other new queens from the hive. These departing queens will also take swarms of workers with them. Once a single virgin queen has the hive and remaining workers to herself she will fly out, mate with a drone, and begin adding new members to the colony. Those virgin queens that left the hive with swarms of workers also find drones to mate with and return to their swarms. However they were formed, the swarms along with a fertile queen will send scouts far and wide in attempt to find a suitable hollow in which to build a new hive.
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Ants have a similar genetic system to bees (i.e., diploid females, haploid males, where the presence of an existing queen inhibits the development of fertility in other females) with some variations due to their pedestrian lifestyle after mating. Fertile females (future queens) and males eclose with wings and there will be mass departures and mating flights of the winged males and females. Once fertilized, the female searches for a suitable site to begin burrowing, sheds her wings and founds a new colony. As the first generation of workers take over food gathering and maintenance of the burrow system different worker castes may begin to differentiate.
In the hymenoptera, all progeny of the one fertilization event will carry genetically identical male chromosomes (because the male is haploid, all sperm carry exactly the same genes) and have 50% of the genes inherited from their mother in common. With this degree of genetic similarity there is no strong selection for individuality that would tend to prevent the evolution of cooperative behavior.
Termites are complex organisms that have formed an obligatory symbiotic relationship with a variety of phytoflagellates who provide the enzymatic machinery necessary to digest wood. They also have a different genetic system compared to bees, where both males and females are diploid, but they have evolved similar kinds of social organization where most reproduction is carried out by a single fertile queen (accompanied by a single male consort who will periodically fertilize her), there may be several castes of workers (who may be of either sex). Other differences between termites and the social hymenoptera are that fertilization occurs only after a male and female together find an appropriate site and together begin preparing a burrow. Hymenoptera are holometabolous, which means that the larvae are helpless. Late instar termite larvae are able to help out in the nest.
When examined from a level of the colony, the more developed insect societies summarised above certainly meet all of the criteria for an autopoietic system.
a. Self-identifiably bounded (demarcated from the environment by membranes, or the entity's components are identifiably tagged): All of the colony-building insects use pheromones to tag and identify members of their own colony, and will often fight with and attempt to kill individuals carrying the wrong tags.
b. Individually identifiable components within the boundary (complex). All of the members of the colony are clearly autopoietic individuals in their own rights. However, they interact with one another to maintain the integrity of the colony against various kinds of invaders including conspecifics from other colonies.
c. Mechanistic (i.e., a system driven by cybernetically regulated exergy fluxes or metabolic processes). Most of the activities of the hive or society are organized and coordinated by various forms of communication between colony members such as pheromones, tactile exchanges, vibration or possibly even visual cues. These serve to recruit help for defense, repair, food gathering, escape from flooding, etc.
d. System boundaries internally determined (self referential). The establishment and maintenance of a recognizable hive odor for the purpose of member vs non-member is certainly a form of self-reference for the colony.
e. System intrinsically produces own components (self production). Special breeding females are responsible for producing all of the individuals forming a single colony.
f. Self-produced components are necessary and sufficient to produce the system (autonomy). Yes. Because all of the individuals forming a colony are the progeny of a single individual they share many genes in common as a resource of the necessary control information for maintaining the colony dynamics.
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Social insects display marked homeostasis in the regulation of their own numbers and of their nest environment. This class of steady-state regulation has been aptly termed social homeostasis... [p. 360]
...
The idea of social homeostasis leads easily to the visualization of the entire insect colony as a kind of super-organism.... Wheeler [1911] saw several important qualities of the ant colony that qualified it as an organism:
1. It behaves as a unit.2. It shows some idiosyncrasies in behavior, size and structure that are peculiar to the species and other idiosyncrasies that
distinguish it from other colonies belonging to the same species.3. It undergoes a cycle of growth and reproduction that is clearly adaptive.4. It is differentiated into 'germ plasm' (queens and males) and 'soma' (workers).
Interestingly, in both the termites and hymenoptera, different species represent all stages from those that make their living as solitary individuals (i.e., with no social organization), through dominance hierarchies to fully eusocial colonies that I do not hesitate to qualify as autopoietic. In terms of total biomass, the extraordinarily successful autopoietic insect superorganisms (ants and termites) are the terrestrially dominant life forms on Earth.
Human economic organizations
Hall (2003; 2005; Hall et al. 2005) presented the argument that at least some human economic organizations are third order autopoietic entities in their own rights. The human economy is an abstraction of real energy fluxes. Individuals as components of organizations use money to purchase the food and fuel they need in order to maintain their lives, and thus measurements and observations of cash flow are a reasonable abstraction of these energy flows from source to sink as high value resources are used in the production of product and dissipated in the form of labor and distribution. Thus, complex dynamics may evolve at a level of complexity involving the economic interactions of humans.
Large economic organizations certainly meet requirements to be considered autopoietic:
g. Self-identifiably bounded (demarcated from the environment by membranes, or the entity's components are identifiably tagged): Members of the organization are typically identified with badges, and sometimes even uniforms. 'Human resource systems" in the organization track memberships, associations, etc. to identify and track members of the organization.
h. Individually identifiable components within the boundary (complex). Individual people are certainly autopoietic entities in their own rights, but they can work together to form and maintain the structure of a higher level organization.
i. Mechanistic (i.e., a system driven by cybernetically regulated exergy fluxes or metabolic processes). Cash accounting, internal processes and procedures, etc. measure and regulate the interactions of organization members to benefit the continued survival and growth of the organization.
j. System boundaries internally determined (self referential). Rules of association, employment agreements, oaths of allegiance to organizational rules, etc. all work to determine who belongs to the organization.
k. System intrinsically produces own components (self production). Processes exist to recruit, induct and train new members.
l. Self-produced components are necessary and sufficient to produce the system (autonomy). Well-established organizations outlive the membership of any particular individuals in the organization.
As in the social insects, human economic human economic organizations show all stages in the emergence of an autopoietic level of complexity ranging from single entrepreneurs, through family
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groups, despotically controlled groups, through to the full panoply of large organizations. Greiner (1998) reviews some of the structural changes organizations pass through, as they become fully autopoietic.
Evolutionary knowledge generated by organizations is tacitly embodied in the physical and procedural structure of the organization (Nelson & Winter 1982, 2002; Dalmaris 2006; Dalmaris et al. in press), and explicitly in organizational documentation (Hall 2003a). Some knowledge specifically relating to the organization is held in human memories, but the bounded rationality (Simon 1955, 1957) of organizational members means that no one person can know everything the organization needs to know in order to maintain itself and respond adequately to meet organizational imperatives in a changing and competitive environment (Else 2004; Nousala et al. 2005; Nousala 2006), thus knowledge required for maintenance of the organization must be distributed beyond the limits of any individual in the organization.
It should be noted that Niclaas Luhmann (1986, 1990, 1995) has described what he calls a form of social autopoiesis in his studies of human social systems. This deviates substantially from the Maturana and Varela (1980) canon in that Luhmann's 'autopoiesis' no longer focuses on the physical interactions of material entities. Basically, it is defined on the basis of an idiosyncratic and highly paradigmatic view of informational relationships rather than energy dynamics between physically definable entities. It is beyond the scope of this paper to attempt to marry the energy driven approach developed here and Luhman's work.
Conclusions
I have explored the circumstances under which organized systems can emerge in a dissipative environment forced to transport energy from a high exergy source to a lower exergy sink and have discussed the importance to establish a proper focal level for analyzing such systems. I have shown that under circumstances between molecular convection and the chaos of a 'short circuit' that the environment will spontaneously evolve towards a near steady state of dynamically cyclical organization able to efficiently dissipate exergy. Where the environmental medium offers suitable possibilities, such systems may evolve to a point where they can be said to have a recognizable duration through time, such that in some of these cases the steady-state dynamical structure may begins to homeostatically self-regulate itself. In suitable environmental circumstances, homeostatic systems may evolve into fully autopoietic systems. Their success and survival is governed by the accumulation of structural knowledge (in Popper's W2) that may develop further through the evolution of mechanisms to persistently codify some of the survival knowledge (W3).
The emergence of at least three orders of autopoiesis has been documented: a first order at the cellular level of focus comprised of macromolecular units and subsystems within a chemical environment; a second order at a level of multicellular organismic focal level comprised of individual cells and living within an ecosystem; and at least two different kinds of third order systems assembled from multicellular organisms as the subunits at similar focal levels. These third order systems include 'superorganismic colonies formed by various species of social insects within the ecosystem on one hand, and human economic organizations formed within the economy.
Not considered due to the limited focus of this work are possible cases of autopoiesis in multispecies assemblages of bacteria (i.e., trophic mats), obligatory symbiotic associations such as between fungi and algae to form lichen and the rhyzospheres involving higher plants, and human social organizations such as clubs and religions that might be seen as a different form of organization than the economic organization. I have also not considered the possible existence of
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orders of autopoietic organization above the third order: e.g., ecological communities, ecosystems, Gaia; or nation states, industrial associations, the economy, etc.
In association with my exploration of the conditions under which autopoietic organization can arise, I have also shown that the evolution and growth of knowledge at any order of autopoiesis is an integral part of the process by which autopoiesis emerges. The current literature on autopoiesis attempts to deal with this issue in highly paradigmatic 'observer centric' language. I find that Howard Pattee's biophysical epistemology and Karl Popper's evolutionary epistemology allow the development of an epistemology of autopoietic organization that should be much more accessible to the main stream of science.
Basically, knowledge in the autopoietic system is the capacity for self-control. This control knowledge exists first in the historically developed dynamic structure of the autopoietic system itself (which exists only in a tiny fraction of the phase space represented by all possible locations and dynamic interactions of the components contained within the physical space occupied by the system). The knowledge is expressed in the way the structure of a particular autopoietic system provides the instantaneous dynamics for and constrains the further trajectories of the system's component parts. This 'knowledge' is a tangible projection of a history of the survival of an autonomously self-maintaining autopoietic state, where the solutions to the problems of life represented by that history populate a different ontological domain from that of the instantaneous physical reality. This 'knowledge' resulting from the constraints of the historically determined instantaneous present state establishes an epistemic cut between what is measured and controlled and the capacity to measure and control.
In Popper's epistemological ontology, instantaneous physical reality and its dynamic state form world 1, whereas the solutions to the problems of life represented in the capacity to measure and control populate world 2. Autopoietic systems may also evolve ways to codify knowledge in compact, energetically degenerate codes as a persistent and abstract representation of control information. In first-order cellular life nucleic acid polymers carry the encoded control information. Using the information requires a complex system for transcription and translation into structural knowledge, which represents a significant epistemic cut between the codified knowledge and its enactment into structural knowledge (world 2), where the control can be applied to world 1. This codified knowledge forms world 3.
Every autopoietic system at any order of autopoiesis must have the world 2 structural knowledge that embodies an instantaneous state resulting from an historical trajectory that maintains system parameters within a part of the phase-space where the entity will continue to be self-regulating. I argue that autopoietic systems of any order may also evolve codification systems that enable knowledge to be accumulated in world 3. In addition to the capability to store codified knowledge in DNA, higher multicellular organisms have evolved mechanisms in world 3 for transferring and storing survival knowledge outside of the body, e.g., trails, pheromones and, most importantly for humans, linguistic mechanisms.
I have argued that in the early evolution of cellular life, cellular components and codified knowledge (DNA) would have most likely been shared promiscuously, which would have impeded the differentiation and evolution of trophic specializations. However, as cellular organization became fully stabilized, and increasingly larger fractions of control knowledge became codified into DNA chromosomes, different lineages could begin to evolve their own specializations and protect themselves from the disruptive activities of irrelevant or inharmonious control information. The downside of encoding control information into chromosomes protected within the cell is that the opportunities for recombination and selection of already tested knowledge in new combinations would have been greatly reduced. Had this protection been fully effective, clonal reproduction
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would have greatly slowed the evolution of favorable gene combinations. The evolution of controlled means of sexual recombination enabled the establishment of biological species, which enabled the proliferation of the diversity of living things we see today.
Not discussed in the present work, but of great interest for further study, are similar issues relating to the dissemination and control of linguistically expressed knowledge at the second and third order of autopoiesis.
The ideas presented here only scratch the surface of what is potentially a very large area for further research.
ACKNOWLEDGEMENTS
My employer, Tenix Defence, has consistently allowed me to work on this project during business hours. From 2002 to mid 2005, additional office and library support was provided via an honorary fellowship arranged by Dr Frada Burstein, Faculty of Information Technology, Monash University. During 2006 my work was facilitated by a National Fellowship in the Australian Centre for Science, Innovation and Society, Melbourne University and by Dr Liz Sonnenberg, Department of Information Systems, Melbourne University, who kindly arranged office space in the Department. Without making any claim that these people agree with my conclusions, many individuals have contributed to the intellectual content of the work and helped me sharpen my expression: Hugo Urrestarazu, Joe Firestone, Howard Pattee, Steven Else, Susu Nousala, Peter Dalmaris, Ken Long, Richard Vines, Tony Smith and a number of seminar participants at University of Technology Sydney, RMIT University and University of Melbourne, plus many others I have interacted with via various Web forums and knowledge management event.
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