Introduction to Cognitive Science
Last Update: 30 November 2008
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7±2 Key Dates in Cognitive Science
What is cognitive science?
≈def the interdisciplinary study of cognition, i.e., of:
language understanding & generation
computational cognitive science = cognition is computable
a working hypothesis:
how much of cognition is computable?
classical symbolic computation
"mind as machine"
express theories of cognition as computer programs
can test theory by running the program
Do computers running such programs actually exhibit cognition?
If not, why not?
contrast with behaviorism:
to get from stimulus/input to response/output
share methodologies across disciplines
What is the mind?
philosophy ≈def search for truth in any field, by rational (logical, scientific) means.
Mind-body problem: What is the relation between mind and brain?
dualisms (e.g., Descartes's interactionism)
monisms (e.g., Berkeley's idealism; materialism/physicalism & the identity theory)
psychological type of a brain state/process is a function of its causal role in the individual's cognitive life
qualia (including inverted & absent)
implementation (cognitive architecture) may be important
Problem of other minds: How do I know that you have a mind?
Theory of Mind, Folk Psychology, & Modularity
BDI folk psychology is a theory we use to explain & predict others' and our own behavior
We explain & predict others' behavior by simulating the others' mind
Fodor's theory of mental modules
Pylyshyn's theory of cognitive impenetrability
logic = normative study of reasoning correctly (i.e., truth-preserving)
cognitive science: how people actually reason
not always correctly!
Wason card-selection task
Tversky & Kahneman on probabilistic reasoning
Johnson-Laird's theory of Mental Models
Rips's theory of Mental Rules
Simon: bounded rationality
AI: computational theories of non-monotonic, default, and defeasible reasoning
Rules and Connections
AI: "computational cognition"
Minsky: make computers do cognitive tasks
Boden: understand (human) cognition using computers
programs as theories/models of (human) cognition
how is cognition possible?
how much of cognition is computable?
What is computation?
Church-Turing thesis: Any algorithm can be expressed as a TM
GOFAI (classical symbolic AI): logic-based
Newell & Simon's PSSH:
a physical system can exhibit cognition
it is a physical
(= physical implementation of a TM)
Fodor's CTM & RTM:
cognitive states/processes are computations over cognitive representations
cognitive representations are a language of thought (LOT),
with a syntax (& maybe a semantics)
Dennett's Intentional Stance:
best to treat complex systems
they were intentional (i.e., cognitive)
deep vs. surface structure;
universal grammar (innate LAD)
competence vs. performance
Connectionism (ANNs): statistics-based
Minsky & Papert's objections
Rumelhart & McClelland's PDP
representation as activation patterns of artificial neurons
Fodor & Pylyshyn's objections:
unconscious inference/tacit knowledge
Dynamical Systems theory: differential-equation-based
Concepts and Categories
classical view: categories as sets defined by necessary & sufficient conditions
Wittgenstein: family resemblances
prototypes vs. exemplars
Lakoff & Johnson:
conceptual systems are metaphorical
based on human body.
long-term, short-term, working memory
AI memory schemata: Minsky's frames, Schank's scripts
Vision & Mental Imagery
Pylyshyn: mental images are propositional
Kosslyn: mental images are pictorial
Gibson: direct perception of "affordances"
Marr: perception requires processing:
primal image, 2.5D image, 3D image
3 levels of psychological explanation:
"computational" (functional): what (I/O)
"algorithmic" (computational): how (algorithms)
"implementation": multiple physical realizations
direct vs. indirect realism
arguments from illusion, time lag
Guest Lecture: Udin
anatomy (structure) & physiology (processing) of brain
McCulloch & Pitts's logical ANNs
is the brain a computer?
Sloman's information-processing theory of grief
suggests possible 4th level between Marr's (a) & (b):
Simon: emotion's role in guiding reason through the limitations of bounded rationality
identity theory: conscious states
Nagel: only a bat can know "what it's like to be a bat"
McGinn: understanding consciousness is beyond our cognitive abilities
Rosenthal: consciousness is meta-thought
Dennett: multiple drafts theory
Chalmers: physicalism is false
are there neural correlates of consciousness?
Rapaport on "Notes towards a Computational Theory of Consciousness",
TODAY (Thurs., Dec. 3), 1:00-3:00 p.m., Bell 224
Metacognition in Non-Human Animals
Guest lecture by J. David Smith
importance of context/the world
Putnam: Twin Earth: cognition is not (merely) in the head
Fodor: Methodological Solipsism: yes it is!
Hutchins/Clark: there are extended cognitive systems; so, no it isn't!
Simon: yes it is
B.C.Smith: no it isn't
Interdisciplinary cognitive science projects (at UB):
Deixis & Narrative
LIN + Neurosci: PET studes of linguistic processing (Jaeger, Lockwood)
LIN + PSY: lexical semantics (Koenig, Mauner)
LIN + AI: computational linguistics (Koenig, Shapiro, Rapaport, Pierce)
PHI + GEO + LIN: spatial ontology (Smith, Mark)
Turing Test & Chinese-Room Argument
Computers will be said to be able to think
to the extent that we cannot distinguish their linguistic/cognitive ability from a human's
Chinese-Room Argument (Searle):
It's possible to pass a TT without really thinking
Pat Hayes has allegedly defined cognitive science as "the ongoing research program of showing Searle's Chinese Room Argument to be false"! (Harnad, cited in Boden 2006:1384)
ultimately, might be a
Copyright © 2007 by
William J. Rapaport