General Understanding of Information

4. Mrz 2011 Informationsphilosophie. Information und urbanes Systeme 1

Information:Brcke zwischen

Philosophy: Philosophy of InformationFakultt 13, Hochschule Mnchen, Winter Semester 2016-2017

Jos Mara Daz Nafra (Universidad de Len, Spain)

A General Understanding of Information

1. Groundingsa) The information age and the language of

information (historical perspective)b) The Frame of the Mathematical Theory of

Communication (film: Communication Primmer)c) Semantic information and Algorithmic Theory

of Informationd) Information in the sciences

2. Information throughout the ladder of complexitya) The progressive perspectiveb) Regressive perspective

3. Presentations

2A General Understanding of Information

The origins of the information concept

Latin and Greek roots Material information case (Hefestos) Observation case (Subject) Speaking or Instructional case (communication)

Platos Forms Otherworldliness Digital communication model

Aristotles Matter and Form Form (actuality) and Matter (potentiality) The individuality of real things. Particular

form: essences General essences: being of species that can be

inductively grasped


Bibliographic tips

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FLORIDI, L. (2010). Information. A very short introduction. Oxford: Oxford University Press.

DAZ NAFRA, J.M. (2011). Messages in an open universe. in Capurro, R. and Holgate (eds.). Messages and messangers. Angeletics as an approach to the phenomenology of of communication. Munich: W.Fink, 195-229.

DIAZ NAFRIA (2011): Information, a multidimensional reality, in Curras and Lloret. Nuria LLORET(2011). Systems Science and Collaborative Information Systems. Hershey PA, USA: IGI Global

DAZ NAFRA, J.M. (2010). Information: a multidimensional concern. TripleC, 8(1), 77-108 [online http://triple-c.at/index.php/tripleC/article/view/76/168].

HOFKIRCHNER, W. (2010). Twenty Questions About a Unified Theory ofInformation. Arizona: Emergent publications.

BURGIN, M. (2010). Theory of Information. Fundamentality, Diversity and Unification. Singapore: World Scientific Publishing.


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LYRE, Holger (2002). Informationstheorie. Eine philosophisch-naturwissenschftliche Einfhrung. Munich: W.Fink Verlag.

DAZ NAFRIA, J.M., et al. (Koord.) (2010). Glossarium BITri: glossary of Concepts, metaphors, theories and problems concerning information. Len: Universidad de Len [online http://glossarium.bitrum.unileon.es/glossary, http://wp.me/pzKNC-66]

DAZ NAFRA and SALTO (2009). What is information? An interdisciplinaryapproach. Special issue TripleC, 7(2) [online http://wp.me/pzKNC-2G].

Bibliographic tips


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information

theory

know ledge

concept

communication

use


Invitation to Complementary Activity

Social Networks (2012): from indignation to change Social Networks (2013): from communication to solidaritySocial Networks (2014): globalization and inequalityglossariumBITri (2015): How to write interdisciplinary papers?

1st - 3rd ed. Sept.2012-2014;4th ed. Sept.2015, Santa Elena, Ecuador

Cooperation: HM - ULE UNED TUW UPSEWith: Prof. R.E. Zimmermann (HM)

Prof. J.M. Daz Nafra (ULE) Prof. P. Hofkirchner (TUW), et al.

Credits: 2 ECTS9A General Understanding of Information

PRIMERE&R Programme


Education & Research programmeInternational Summer Academies

Support: EU (under request)Period: 2017-2020Venues: Spain, Austria, Greece, Germany

I. Groundings (the development of the information understanding)

0. Towards a general understanding of information

1. Development of the information concept: Plato, Aristotle, Middle Ages, Modernity, (technique and physics)

2. General understanding of Information3. Mathematical Theory of Communication4. Algorithmic Theory of Information5. Information in the sciences


I.0 Towards a General Understanding of Information

In the Information Era we should be able to understand what information really means (comparison to the Iron Era: iron vs cupper)

The Nature of information is not solved Information can be considered as something

mediating between Objects and Subjects To this end, a general understanding of Objects

and Subjects is also needed.


I.0 Information concept (immaterial)

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TimeInformation

t1 t2 t3

Subject of the change (in the awareness)

Object: In opposition tothe subject ofthe change (awareness)


(0) Information concept (tangible)

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Time

t1 t2 t3

Information

Subject of the change

Object: In opposition to the Subjectof the change(model + hammer)


(0) Clarifying

Form: a particular configuration/Gestalt produced in the subject.

Subject: System which can adopt potential changes Object: what remains stable (in front of the subject)

causing the changes in the subject ~ Model Time: Running of the procedure (i.e. change of the

subject). Past: actual; Future: potential O. vs S.: In strict sense, both sides change during the

process (O. & S. are only relative regarding the corresponding change)


I.1 Evolution of the information concept (a) Plato vs. Aristotle

Plato (idealistic tradition) Form is what exists in the first place and it is out of the

world, otherworldliness (a-spatial, a-temporal). Forms are participated by appearances (phenomena) and

souls. By these means the observer can really recognize the forms.

The innate ideas must be awaken (the observer recognizes what already was in his soul).

The observer returns to the truths, slept within himself.


Plato: World of forms

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Ideas

Form AppearanceI

Decontextualizing: Die existing Forms belong to the otherworldliness (a-

spatial, a-temporal)


Observer

Plato and Signal Theory

From the viewpoint of the modern signal theory (Digital Transmission): Ideal of transparence

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Si{S1, S2, SN}

Noise

Si Compared with{S1, S2, SN}

Si


(b) Aristotle

Form: embrace the essential properties of a thing

Matter: embrace the potential changes Every thing has its own form, its own essence,

which correspond to its being. The reality of a thing relates to its details, its

differences (dish in Plato and Aristotle) There is a general being, which corresponds to

the being of the species. One can inductivelyrecognize them by observation.


(c) Information concept (Middle ages)

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Augustine of Hippo (IV c.): Credo ut intellego

Anselm (XIc.): Fidens quarens intellectum endeavor towards understanding

Aquinas (XIIIc.): Reality is understandableHermeneutic: Interpretation Activity, Imagination Ability

God Belief

RevelationTruthRequirement: Noiseless channels


(d) Information concept (Modernity)

Reformation and Enlightenment (XV-XVIII c.) received the clarity and transparence of Augustine (transparency unmediated, no distance)

Physics (XVII c.-) of that time (until 19.Century) had control over space, but not over time:

Absolute, true, and mathematical time, of itself, and from its own nature, flows equably without relation to anything external. (Newton, Scholia to the definitions in PN-Principia Mathematica, Bk. 1, 1689)

Time was left free to philosophy, where it was not considered as an independent concept, but as something inherent to processes (Leibniz, Kant, Heidegger, Bergson).


Ancient Telecommunication

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Polybios (2nd Century BC)

Hellenic optical telegraphy (Tower system)

Sextus Julius Africanus (3rd C. AD)

Roman optical telegraphy (Tower system)

(e) Modern Telecommunication

The most important difference between early and modern telecommunication (since XIX c.) concerns transmission speed.

Until end of the XIXth c. Information-Transmission was understood as an immediate event: The time of the transmission process disappears. The mediating space correspondingly disappears, One can only speak of the process of the E. and R.,

which must be synchronized.


(f) XIX C. Physics

Late 19th Century Physics (e.g. Maxwell) understood the being of time as attached to processes: Entropy represents the irreversibility of

processes (Time: inevitable and unidirectional run of the processes)

Physics of fields understood Processes in Space & Time > Change in the understanding of EM transmission


(g) Mathematical Theory of Communication (Shannon)

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Emitter Coder ReceptorDecoder

Original message Codified

Message

Decoded message

Noise

Channel

Noiseless Channels (magische Kanale)

This viewpoint (and alongside the oblivion of space) have many consequences in the actual game of the globalization:1. It technically enables the run of the economical processes at the international

level.2. It technically enables the hiding of power relations.3. Instead of facilitating social achievements, the power constellation (economical

domination) can easily reconfigure the network of economic agency.


(h) Computer technique and Cybernetics, 20th C.

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1940s Pioneering work of Alan TURING, J. VON NEUMANN1950s Machine-model of neuronal systems (McCULLOCH et al.):

Connectionism 40s-60s First Cybernetics (N. WIENER, R. ASHBY) and System Theory

(L. von BERTALANFFY, CHURCHMANN)60s-70s Artificial intelligence (NEWELL, SIMON, MINSKY): Symbol

Processing (e.g. LISP) > MACKAY 60s-80s Codification and Pattern recognition (KOLMOGOROV,

SOLOMONOFF, CHAITIN): Theory of complexity and Algorithmic Information Theory

1970s- Second Cybernetics (MATURANA, VARELA, van FOSTER) and complexity theory (PRIAGOGINE, MORIN, ZIMMERMANN)


I.2 Aspects of a general understanding of information

Semiotic: Theory of signs and symbols (Morris, 1938) The Syntax concerns the occurrence of individual information

units and their mutual relations. The Semantic concerns the meaning of information units and

their mutual relations. The Pragmatic concerns the effect of information units and

their mutual relations.

A complete understanding of information unfolds in the dimensions: Syntax, Semantic and Pragmatic


I.2 Aspects of a general understanding of information

Timely aspects of information (Weizscker): Actual: already present and effected information Potential: the possibility to obtain actual information.

Namely, the difference between past and future is grasped by the information concept.

Actual information exists factually, whereas potential information exists only in relation to possibilities.

Therefore Actual Information can be regarded ontologically, whereas Potential Information is intrinsically relational.


(I.2.a) Example: information measurement through unveiling a card

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32 Cards: 8 cards / type (clubs, spades, hearts and diamonds)

1-8 Clubs 1-8 Spades 1-8 Hearts 1-8 Diamonds

Mnimal # of questions in average- for yes/no answersQ1: Black?

A1: NoQ2: Heart ?

A2: NoQ3: > 4?

A3: NoQ4: > 2?

A4: YesQ5: 4?

A5: Yes


I.2(a) Syntax and Probability

I = ld (N=No. choices) = - ld (1/N) = - ld p = - log2 pExtensive measure: I-Content of a dual system: I(cont) = I(1) + I(2)

Probability & potential syntactic information are equivalent concepts for the quantification of possibilities.

The concept of probability can be regarded as a sub-concept of a general information concept.


I.2(b) Semantic and Pragmatic

The necessary entanglement of semantic and pragmatic aspects of information within semantic-pragmaticsoffers the possibility to an objectification of semantics.

Context always presuppose context, Inf. always presuppose Inf.

Information exists only relative with respect to a difference between 2 semantic levels.

The philosophical key issues in the research of the I-concept concern the epistemological and ontological aspects. Both questions are actually interdependent.


I.3 Telecommunication Information theory

Shannons Information-EntropyIi = - log2(pi)P={1/2, 1/4, 1/8, 1/8 }; Dicep1=p; p2=(1-p)

Codification theoryIn order to transmit the maximal amount of information content in the minimal time: Redundancy-free Source (Morse, 4 symbols ex.)Huffman method: Lk~Ik


I.3. Telecommunication Information theory

Firstness (Erstmligkeit) and ConfirmationThe word information, in this theory, is used in a special sense that must not be confused with its ordinary usage. In particular, information must not be confused with meaning In fact, two messages, one of which is heavily loaded with meaning and the other of which is pure nonsense, can be exactly equivalent, from the present viewpoint, as regards information... In the theory of communication, information relates no so much to what is said but to what could be said. information is a measure of the freedom of choice communicators have when they select a message. (Weaver)

The telecommunication I-Theory treats Information under syntactical aspects


I.3 Telecommunication Information theory

Is there information without confirmation? Phenomenon, manifestation underlying reality Perception, stating that something is the case requires

confirmation A confirmed phenomenon provides no information

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Information

Confirmation (Redundancy)

Firstness (Novelty)

0 11/2

1 0

Shannon (MTC)

Pragmatic-semantics


I.4 Semantical approach to Information

GDI (data + meaning) is an instance of information (understood as semantic information) if and only if1) consists of n data, for n12) The data are well formed3) The wellformed data are meaningful

Dd datumx being distinct from y, where x and y are two uninterpretedvariables and the relation of being distinct as well as the domain are left open to further interpretation.


I.4 Semantic approach to Information

Environmental information2 systems a & b coupled in such a way that as being F is correlated to b being G, then carrying the information for the observer of a the Information that b is G.

Factual semantic informationp qualifies as factual semantic information if and only if p is (constituited by) well-formed, meaningful and veridical data


I.4 Algorithmic Information Theory

The algorithmic information content is a measure of the syntactical diversity or complexity

The very shortest description: Ialg(s)=L(pmins) Differences with the shannonian concept:

1. Syntactic vs. Minimal complexity as usage of that semantic providing a minimal syntactic effort.

2. Potential vs. Actual Information3. Objective vs. Relative quantitative concept: Complexity in relation

to regularities that are readable from a selected semantic space.

The algorithmic I-content measures actual I. under both syntactic and semantic aspects. It represents no absolute quantity but a relative one.

It is not computable, i.e. it is related to subjects.37A General Understanding of Information

I.5 The information concept in the sciences

System theory (Bertalanffy, Wiener) S.S. (Luhmann), B.S. (Maturana u. Varela) Th. of open systems (Weizscker) Linguistics (Chomsky, Eco) Economy (N. Georgercu-Roegen)



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Objective or subjective?

Ontological category

independent

Relational concept,

dependent on:Subjective

concept

GeneralAbstract Human

Subjectivity or Intencionality

Theory of Objective

Information

StonierGitt

Ciber-netics

WienerGnther

Algorithmic Information

Theory

SolomonoffKolmogorovChaitin

Structure and process

Structure and behaviour,Evolution

Unified Theory of

Information

HoffkirchnerFleissnerFenzlLazloBrier (Cibersemiotics)

Release mechanism

Karpatschof(ActivityTheory)

Measu-rement

General Theory of Measure

ment

v. NeumanBrillouinMhler

MTC

ShannonWeaber

Uncertainty,probability

Interpretable and

generating

Objecti-vised

Seman-tics

WeizsckerLyre (Quantic T. of Inf.)Matsuno (Diacronic I.)

BiologyMaturana, Varela

2nd O. CiberneticsV. Foerster

CognitiveDretske

mental DifferenceFlckiger

Selfreferent. Sist T.Luhmann

Cognitive Science

Semantic Theories of Information

Bar-Hillel & CarnapSituational

Barwise, Perry,Seligman, Israel

TruthfulnessFloridi

Dependent of

RelevanceDecision T.Racionality T.

Inf. HermeneuticsCapurro

Intersubj. KnowledgeOeser


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SyntacticalHow is it expressed?

MTC (Shannon, Weaver)

SemanticWhat does it represent? Is it true?

PragmaticWhat value does it have?

Quantum Theory of Information

and Measurement (Lyre,

Mahler)

Holographic Universe (Bekenstein)

SyntacticalHow is it expressed?

Logical empiricism (Bar-Hillel,

Carnap)

Cognitive constructivism(Dretske)

Situational semantics (Barwise, Perry, Seligman)

Algorithmic Information Theory (Solomonoff, Kolmogorof, Chaitin)

Objectivised semantics (Weizscker, Lyre) Theory of Objective Information (Stonier, Gitt)

Unified Theory of Information (Hoffkirchener, Fleissner, Fenzl, Lazlo, Brier,)

Fuzzy semantics (Zadeh, Prez-Amat)

Theory of Self-referential Systems (Luhmann)

Aesthetic Theory of Information (Bense,

Moles)

Theory of purpose-oriented action (Janich)

Activity Theory (Karpatschof)Activity Theory (Karpatschof)



II. Information in the physics

Inf. is still not a physical concept as E, M, S, T But may it become a Central concept?1. Thermodynamics

Principles (1., 2., 3.)

2. Field theoryAppearance and Perception

3. Quantum theoryMeasurement theory

4. Space-time TheoryRelativity theory, Quantum Gravity


II.1 Thermodynamics

1. Entropy and 2nd Principle (1., 2., 3.) Principles

dS = Qrev/T, dS 0 Qirr irreversible Processes

BOLTZMANN, MAXWELL, GIBBS: phenomenologic-macroscopic Th. microscopic-mechanical

BOLTZMANN (1896): Entropy as quantitative concept: S = k B lnp S = k Bpilnpi

Information entropy and thermodynamic entropy are formal identical. Both quantities are equal, if one considers Entropy as potential Information, as quantity of the number of possible micro-states in a macro-state.


II.1 Thermodynamics

2. Maxwells Daemon

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The molecules have the same average speed

different average speed


II.2 Field theory (natural limits of information)

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Nature loves to hide

Heraclitus of Ephesus

S

Observed reality (Object)

Observer(Subject)

D

Bounding surface

Arbitrary complexity

22

22 ,1,

tt

vt

rr

Structure of the phenomenon


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),,,,(

),,,,( wo

11

11

11

nnnMM

nnn

n

N

nn

N

nMM zyxvuG

zyxvuG fTnn ff

Phenomena (manifestation) Wavefunction

Complexity of the phenomenon (manifestation)? = Conveyed information?1) The details are regularly distributed (~/2)2) The highest gathered information does not depend

on the accuracy of the observation but on the dimension of the ( a2)

3) Theres only a univocal solution for a discrete projection over a given bounding surface.

Bounding surface(Huygens Principle)

Source:(Real or predicted equivalent)



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z

x y

a

Observation domain

Domain of prediction

E E

Domain of prediction OBS

OBS

d

,min/

][

Projection

1Projection

fT

TTTf

f

Domain of observation

Arbitrary structure

Polyedron of projection

1) The field of an arbitrary structure is computed on an observed domain.

2) From this observation a projection over the perfect polyhedron is determined.

3) The field of both the original structure and the projected in the prediction domain are equal.

Uniqueness solution for the selected projection distribution

Trans-Operator: f



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Projection-Operator: s

Trans-Operator: s



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It is possible to speak of potential and actual (Weizscker)

II.3 Quantum theory (Limits of information)

Zeit


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(II. Appendix) Perception: Consequences of the physical limits in the human perception

a) regular hole or irregular coloured protuberance

b) irregular protuberance or regular coloured hole


The preferred perceptions tend to be those corresponding to the simplest configurations (Ockams razor)

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(II. Appendix) Perception

Examples of ambiguos perception


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Solution of ambiguities

f

N

, 1N

... NN

Initial hypothesis

G2-1 G1-1

G2 G1

Ob{ k1 }

},{ 1kkd ss

K{ ks } Ob{ k2 } Ob{k3 } Ob{

kN }

G3-1

G 3

GN-1

G N

(II. Appendix) Perception


III. Information in Biology

The actual decoding of human genome brings in biology the information theoretical aspects to the fore1. Genetics

Theory of heritage, Molecular-biology

2. Evolution theoryAppearance and Perception


III.0 Historical remarks

Darwin: tiny germs / mutations Galton: lineages (used in ontogenesis)

Mendel (1856): a carrier for every individual character Correns, Tschermark, and de Vries

rediscover the heritage theory, Molecular biology

Miescher (1869): nucleotide of cell kernel (DNA).Mller (1925, Mutations of Drosophila)Bateson: Genetics, Johannensen: Gen


III.0 Historical remarks

Avery (1944): Transformations as f(DNA) Hershey and Chase: experiment with bacteriophagusSchrdiger (1944): a-periodical crystal Watson and Crick: Nature of the DNA MoleculeNot the chemistry of the DNA but the molecular structure: Information theoretical paradigm


III.1 Genetics

Central dogma of the molecular biology 4 Bases:

(A) Adenine, (G) Guanine, (T) Thymine, (C) Cytosine Chargaffs rules: {A & T}, {G & C} equivalent molar amountsThe DNA heritage-molecule represents in its nucleotide-structure a genetic code i.e. syntactical information- for the production of RNA and Proteins.

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DNA RNA PolypeptidTranscription Translation

Since discovery of Retrovieren

Replication


IV. Information throughout the ladder of complexity

Progressive Perspective (Emergence)The force, through which the development of the individual occurs, is the same force, through which different organizations at the earth come into existence. (Kielmayer, c. 1790)

Regressive Perspective (computing the origins)What we call nature is a poetry enclosed within a secrete enigmatic writing. If the enigma were unveiled, we would recognize the spirits Odyssey.(Schelling, STI, 1800)

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Purpose:1. Understanding the emergence of new beings within the world2. Understanding cosmological and epistemological evolution as

computation


IV. 2. Understanding emergenceDoes Emergence exists as something new in nature?

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Emergence can be understood as the real consequence of agents actions on its own level (Zimmermann & Daz 2012; Daz & Zimmermann 2012, 2013)

Agents can be generalized by extending S. Kauffmans idea of autonomous agency as systems capable to perform thermodynamic cycles (from pre-geometry, to physics, to chemistry, to biology, to conscious life, to sociality)

Ontological irreducibility with respect to the parts constituting the agency: formation of new classicity, which in turn is related to the rules of interaction/organization (new order of existence with its spatial laws of behavior, Alexander 1920)


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It properly requires rephrasing the philosophical concepts of choice(from an (un)determined set of possibilities), meaning (related to the sense of beings, ontological disposition of a real being) and normalization (as combined effect of a critical mass of interacting parts) throughout the ladder of complexity.

The fundamental attributes of Energy, Matter and Information, Structure need also be reviewed as fundamental elements for the constitution and evolution of systems.

Potentiality

Energy

Information

Actuality

Matter

Structure

IV. 1. Understanding emergenceDoes Emergence exists as something new in nature?


IV.1. Understanding emergence Does Emergence transcend classical models of computation?

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Classical computation model is restricted by Turings halting theorem bzw. Gdel incompleteness (Chaitin), thus it represents a case of systemic closure, which is indeed needed for the constitution of an effective agency (for instance, Kuhns normal science). Hence it properly models closure.

Emergence can be visualized as the need to overcome the limitations of an algorithmic closure referred to the relations governing the system, which in turn can be mapped into Turing machines as long as they are in normal operation.


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What computation model can better represent real emergence?i. Quantum computation (Zizzi 2005)ii. Cellular automata (Wolfram 2002)iii. Computational ecologies (Mainzer 2004), etc.

In the human: perception, scientific discovery, etc. requires creative abductions which represent a most distant case to classical computing: epistemological emergences.

How can we rephrase the relation between physics-aesthetics-ethics?

Physics

Aesthetics

Ethics

IV.1. Understanding emergence Does Emergence transcend classical models of computation?


IV.1. Understanding emergenceAutonomous and fundamental agents

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We have rephrase the problem in terms of proper agency

1) Generalized Autonomous Agent (S. Kauffman 2000, 2006): system able to achieve a new closure in a given space of catalytic and work tasks propagating work out of non-equilibrium states and playing natural games according to constraints of its environment.

2) For enabling a systematic view of the universe: the fragmented vision of quantum- and relativistic physics has to be overcome. Thus we set off from the level of pre-geometry described in terms of spin networks(R. Penrose) and the related developments of quantum gravity. Good candidate: L. Kauffmans knot theory visualize spin networks as

knots acting on knots to create knots in rich coupled cycles (metabolisms)

Braunstein-Gosh-Severi (SVR) entropy allows to put forward generalized conditions of autonomous agency in the sense of S. Kauffman.


IV.1. Understanding emergenceAgents dynamics

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3) Agency dynamics: mapped through game theoretical applications (Szab & Fth 2007); Evolutionary system dynamics: mapped through category theory (Zimmermann 2011). Utilizing the skeleton-of-the-universe-view (Zimmermann 2004), we can set off from the fundamental level of quantum gravity: inserting steps of a hierarchy of complexity into the functor diagramfrom topological quantum field theory:

4) Fundamental attributes of the universe

Potentiality

ENERGY: to perform work

INFORMATION: to select/utilize work in the benefit of the organization of the system

Actuality

MATTER: actualized (stabilized) energy

STRUCTURE: actualization of the organization potential


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IV.2. Generalizing the concept of information

Generalized 2nd principle of thermodynamics: entropy/information of a closed system increases

(Potential) information: what the observer ignores about a situation(Boltzmann) Entropy: what the observer ignores about the

microscopic constitution of a system

Example: steam enginethis is a non-self-organizing systems working for itself,but for another system

INFORMATION as potentiality for building constraints and affordancesthat enable propagating work.


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IV.3. The Progressive Perspective:From Spin Networks to Social Networks


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IV.3. The Progressive Perspective: The Odyssey of Autonomous Agency

Step 0: spin networks


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Step 1: Elementary particles (proton: stable combination of quarks)Step 2: Atoms and Molecules



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Step 3: Starts and Planetary Systems



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Step 4: Complex molecular structures and living beings (proton channels)



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INFORMATION as potentiality for building constraints and affordances that enable propagating work

Step 5: The emergence of seeing (Euglenoid cell)



IV.4. The Regressive Perspective: Acknowledging the World

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In Cognitive and social contexts, we deal with agents who have self-reflection and try to reconstruct objective situations from essentially limited information (Daz 2011). Basic level: animal perception. We introduce: hermeneutical agency (HA), defined in terms of observation-

interpretation cycles (sensing reality Zubiri).

The HA can be visualized in thermodynamic terms: abductions as reduction of (apparent) representation complexity (neg-entropy) or increase in the probability of interpretation with respect to given constraints (maximal likelihood). Semantics as interpretation tools, which evolves from the very sense of the being (means to reproducing itself, and to evolving); from objective- to reflective- response.

Semantics are only relatively closed. Openness becomes clear when an epistemic emergence is needed, rooted on ontological constraints (Levy-Strauss).


IV.4. The Regressive Perspective:The problem of seeing


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IV.4. The Regressive Perspective:Animal vision

Additional constraints of vertebrate vision:


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a) b)

IV.4. The Regressive Perspective:Animal vision


IV.4. The Regressive Perspective:Physical limits of seeing

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Hence, seeing is necessarily Hermeneutical We need sensing reality (information/data) We need organising sensing (theories/computing)


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IV.4. The Regressive Perspective:Hermeneutical agency (computational mapping)

s N, 1

N... N

N

Initial hypothesis

G2-1 G1-1

G2 G1

Ob{ k1 }

},{ 1kkd ss

K{ ks } Ob{ k2 } Ob{ k3 } Ob{ kN }

G3-1

G 3

GN-1

G N

Application of observations (corresponding to manifestation of modality 1, 2,.. )

Gi : allows to derive the manifestation of modality i from an interpretation of the object, s.

Gi -1: allows to make aninterpretation of the object sconsistent with observation i

Truthfulness criterion

Iteration Interpretation output


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Conclusive remark concerningInformation and Emergence

By using the given conceptualization of the fundamental attributes(E, M, I, S) emergence can be mapped from the pre-geometrical level to the social one;

It requires at the fundamental level an unified perspective (quantum gravity)

The emergence is visualized as consequence of agents action at its own level causing new classicities (space-time, forces, particles, molecules, organisms, humans, societies), related to the rules of interaction/organization.

Hermeneutical agency requires rephrasing the relation between physics, ethics and aesthetics (normalization, meaning, choice).


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