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Theoretical Issues in Psychology
Philosophy of Scienceand
Philosophy of Mindfor
Psychologists
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Chapter 8Modern approaches to mind (2)
• Neural networks and connectionism• ‘Classical’ versus connectionist architecture• The third contender: dynamicism• Is there need for ‘mental representations’?• Naturalism, reductionism and folk psychology
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Neurophilosophy (the Churchlands)
Contrary to Fodor’s ideas:• For answers to philosophical-psychological questions turn to the neurosciences (empirical knowledge - naturalism).• No autonomy for psychology.• Brain-based view of mind: ‘mind is brain’ (but no mind-brain identity).• Eliminate folk-psychological concepts.• Against sentential (propositional) LOT-view of knowledge.• No solipsism, but evolutionary adaptation.
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Model of a neural network
• Set of nodes and connections between them.• Activation spreads through the network.• Giving weights to the nodes.• Three layers: input, output, midden layer of hidden nodes.• Network learns by adjustments of weights.• According to some learning rule (‘Hebb rule’).• Does the training by itself, is tuned to the environment (isnot pre-programmed).• Maintains fault tolerance, graceful degradation (functional persistence), and satisfies soft constraints (all unlike programs).• Knowledge/representations is/are distributed over many connections.• Network is model of human mind: ‘connectionism’.
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Working of a (quasi-neural) network(here, a network of a submarine, learning sonar signals)
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Activation space and prototypes
• Learning to recognize is forming a prototype, a hotspot in a vector or activation space.• A concept is a prototype (not a symbol string).
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Connectionism
• (Quasi-)neural networks:• ‘neural’ patterns of activation (versus symbols and
inborn rules);
• online selforganisation (versus offline programs);• support cognitive tasks.
• Basic cognitive processes (formation of representations) are patterns of activation (not manipulation of symbols).
• Cognition is basically pattern recognition. • Neurophysiology, c.q. neural networks, explains
cognition: ‘cognitive neuroscience’, cognitive theories which are neurological plausible and naturalized:• no functionalism;• no autonomy for psychology.
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• Human brain has: 100 billion neurons = 100.000.000.000 (1010).
• Every neuron has: synaptic connections with 10.000 (104) other neurons.
• In a human brain: 1014 synaptic connections.
• Weight of each connection can have a value of 1 out of 10.
• Thus human brain can contain: 101014 = 10100.000.000.000.000
cognitive configurations(cfr. total elementary particles in universe estimated 1087).
Representational capacity of human brain
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Symbolic versus connectionistic systems
Fodor: thinking is characterized by productivity, systematicity,i.e. a continuous recombination of discrete symbols: compositionality, like building sentences with words: requires formal structure (networks lack structure and are not strong enough to simulate cognition; leaves you with nothing more than a plain associationpsychology);so, LOT is ‘the only game in town’: thinking occurs in a formal language; the only explanation of structure.
Connectionists (a.o. Smolensky): thinking is network activation, compositionality is a by-product of networks: ‘functional compositionality’: doesn’t need a symbolic architecture; productivity of language is not the only possible productivity (Churchland).
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Third Contender: Dynamism: ‘mobots’ and dynamic systems
• Dynamic coupling of organism and environment.
• Activity in environment (no inner representational
domain).
• Online interaction (no innate structure and programs).
• Evolution and time (no static representations).
• Adaptation.
• Dynamic system (no representational structure: LOT or
patterns of activation).
• Cognition is like playing tennis, rather than chess.
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Dynamism: mobots
Mobots : internal representations
and computations redundant.
Rodney Brooks: robot with
response systems, direct
interaction with environment,
without central representations.
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Dynamism: Watt governor
Cognition is on-line real-time interaction with the environment – Watt governor, continuous following and control of behavior and environment; reciprocal causality.
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Mental representations redundant?
The absent and the abstract:• there are ‘representation-hungry’ situations.• that require higher cognitive functions like abstract thinking, imagination and reflection.
• Direct coupling mainly in sensori-motor functions.• External symbols for higher cognitive tasks (planning, abstraction).• ‘Active externalism’ (extended mind, Ch 9.4): for some cognitive tasks we use external instruments, e.g., paper and pencil, graphical devices; books, internet.• ‘Leaky cognition’: brain and environment cannot be separated.
Andy Clark (1997, 2003)
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Naturalism and neurophilosophy Churchland
Naturalism: representation is biological phenomenon, product
of evolution.
Cognition is pattern recognition, not symbol manipulation.
Language appears late in evolution, therefore no LOT.
Functionalism is a conservative ‘cheap# explanation.
Folk psychology (beliefs and desires) stagnating program,
isolated from scientific progress.
Folk psychology eliminated and replaced by neuro-speak.
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Naturalistic (neuroscientific) explanations of:
• knowledge as coded in connection weights;
• representation and intentionality as processes in the
brain;
• sense of self;
• morality as cognitive skill; role of oxytocine in building trust
and love.
Churchland: Naturalism and neurophilosophy
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Eliminativism and folk psychology
Folk psychology (‘belief-desire’) is a kind of theory, explains behavior (Fodor + Churchland).
Fodor: in principle correct theory:• beliefs and desires exist really as symbol structures in LOT;• are causes of behavior;• folk ps. vindicated by CTM;• intentional laws, generalisations, and predictions indispensable: folk psychology is successful predictor;•intentional realism.
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Eliminativism and folk psychology
• Churchland: folk psychology obsolete theory:• stagnating program (Lakatos);• no progress, no connections with current development in
science;• replace by neuroscience;• eliminativism.
• Clark, Dennett: folk psychology is not a scientific theory, • beliefs and desires only descriptive (‘intentional stance’), not internal causes (‘design stance’), not literally true;• different explanatory aims; different level from neuroscientific explanation;• instrumentalism.
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CTM Connectionism Dynamic systemsFormal, syntactical rules, symbols
Weights and activation patterns
Coupled co-evolving systems, developing over time
Preprogrammed, no real development
Self-organisation, learning through adapting weights
Evolving through state space, circular causality, continuous adaptation
Brittle program rules Graceful degradation under damage
Smooth mutual adaptation
Structured, language-like architecture, concatenating discrete symbols
‘Associationism’ Development in time
Productivity and systematicity through compositional architecture
Functional compositionality
Trajectory through state space
Functionalism, autonomy for psychology
Reductionist, (more or less) brain-like cognition
Emergent properties of organism-environment system, and development
Representations are symbolic structures
Representations are activation patterns
No representations needed
Solipsism, self-contained mind
Representations are products of interaction with environment
Body mind and world part of a single system