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Preview of "Cog1-2008F-01-Foundations1.ppt" Preview of "Cog1-2008F-01-Foundations1.ppt" Presentation Transcript

  • Foundations of Cognitive Science !! Cognition - a working definition: Cognition 1 "! The study of mental representations and processes involved in the acquisition, Foundations storage, retrieval, and use of knowledge. Roberto G. de Almeida Department of Psychology Concordia University Roberto.deAlmeida@Concordia.ca http://alcor.concordia.ca/~coglab Fall 2008 2 What do these figures represent? One possible interpretation: Two similar cubes…different perspectives! 3 4
  • Assumptions: Your visual system is equipped to “rules”! extract 3-D information from one arrangement of lines, but not the other… y! “z”! x! A “3-D from 2-D Rule” If lines meet at a given point, interpret as 3-D A “Grouping by similarity Rule” It relies on certain properties of the vertex of an object Interpret similar objects as having “object” (line arrangements, vertices) and it the same orientation in 3-D relies on its own “rules” to assign a global interpretation to the line drawing ! 5 6 Types of knowledge Types of knowledge !! Cognition - a working definition: !! Knowledge: explicit or implicit "! The study of mental representations and "! Explicit: processes involved in the acquisition, !! Declarative memory: semantic memory, episodic memory storage, retrieval, and use of knowledge. #! Semantic: Common knowledge of the world, concepts #! Episodic: Autobiographical, personal experience, own "! Knowledge: explicit or implicit view (including false memories) 7 (Loftus, 1997) 8
  • Types of knowledge Representations & processes !! Knowledge: explicit or implicit "! Implicit: !! A bunch of things: #! Whatever enables you to perform cognitive tasks without having to rely on your declarative memory: #! Procedural-type memory: rules, mechanisms, perceptual knowledge/processes, grammar, etc. #! Mostly, unlearned (by hypothesis, innate) #! If learned, automatic (well practiced) 9 10 Representations & processes Representations & processes "! Knowledge-based behavior/processes "! Rule-governed behavior/processes !! Processes driven by explicit goals, explicit !! Covert processes knowledge (semantic/episodic), intentions !! Processes that rely on implicit knowledge Claude Lorrain (1600-1682), “A seaport at sunset”, Louvre, Paris John Sloan (1851-1951), “Spring Rain” - Delaware Art Museum 11 12 View slide
  • The fundamental concepts Mental Representations !! Descartes, Hobbes, Hume: "! Representations "! Mental Representations are Ideas, Mental Processes are !!“Things in the mind that stand for “Calculations” (Computations) things in the world” !! They are “language-like” !! They are abstract !! They are symbolic They are the very elements of "! Mental processes !! thoughts, cognitive processes !! Operations over representations [CHAIR] !! “Computations” (or “activations”) of representations 13 14 Cummins, 1991 Mental Processes as Computation Mental Processes as Computation over Representations over Representations !! Modern view: Perceptual and cognitive systems (some) work as a function of the “laws”/”rules” they follow !! Right! John must be married to Mary !! Consider the following: "! Suppose you know that John is either married to !! We can represent this by equations (with Mary or to Susan. special, logical terms “or” and “not”) "! And then suppose you discover that John is not "! (1) Married (J, M) or Married (J,S) married to Susan… "! (2) not [Married (J,S)] "! What can you conclude? "! (3) therefore, Married (J,M) Pylyshyn, 1999 15 16 View slide
  • Mental Processes as Computation Mental Processes as Computation over Representations over Representations !! Notice that (3) follows from (1) and (2) regardless !! The process is carried out just in virtue of the “content” of the parts of the equation (except of its form (or syntax or structure)! for or and not) "! That is: computations over symbolic !! Thus, replacing (1)-(3) by the meaningless letters P representations are operations driven by rules and Q should yield the same effect: (syntax) "! (1’) P or Q –!(1) Married (J, M) or Married (J,S) !! We can think of higher-order thought processes (e.g., "! (2’) not Q reasoning)… –!(2) not [Married (J,S)] !! We can think about computations within specialized "! (3’) P –!(3) therefore, Married (J,M) cognitive systems - such as Language, Vision… !! The idea is that behind most perceptual or cognitive processes there are sets of rules governing the !! The process is carried out just in virtue processes of its form (or syntax or structure)! Pylyshyn, 1999 17 18 Levels of Explanation Cognition = Neurophysiology? !! Notice that I haven’t talked about the physical device in !! Notice that I haven’t talked about the physical device in which those representations and processes are which those representations and processes are implemented... implemented... E.g.: reading a word aloud !! Are our explanations intrinsically dependent on the nature of this physical device? !! Should we reduce the cognitive explanation to a neurophysiological account of brain states? !! Would an anatomical classification suffice? 19 20
  • ! Cognition = Neurophysiology? !! Notice that I haven’t talked about the physical device in which those representations and processes are implemented... Are our explanations No! !! intrinsically dependent on the nature of this physical device? No! !! Should we reduce the cognitive explanation to a neurophysiological account of brain states? !! Would an anatomical classification suffice? No! What is missing, then? How can we account for brain function (mind) without appealing to neurophysiology or neuroanatomy alone? 21 22 !!The behaviorist machine: !!One and only one state: #! For every input (a dime) a response (a Coke) !!The cognitivist machine: !!Two (or more) possible states: #! Outputs depend on: #! 1. Input #! 2. The machine’s current state given 1 Fodor, 1981 Fodor, 1986 23 24
  • Functionalism and Cognitive Explanation Turing Machine Alan Turing (1912-1954) !! MachineFunctionalism: !! The behavior of the machine can be explained as a function of #! the machine’s (internal) states #! the machine’s causal structure !! To understand the machine (or human brain, or the Martian’s heart) we have to understand its internal functions, the “laws” that guide its behavior 25 26 Turing Machine Turing Machine !! Machine’s computations (processes): "! Read symbols from the tape (B, 0, 1) "! Write symbols on the tape (B, 0, 1) "! Move (L, R) !! Machine’s representations: "! Symbols !! In sum: Machine reads a symbol, writes a symbol, and moves left or right, according to its states specified in the table (the program) 27 28
  • Turing Machine Marr’s Three Levels !! Computational theory: !! Key ideas: "! The goal of the computation, what it is "! an information processing system (a supposed to be about or to solve (e.g., physical system) can “behave” just in Attention, Sentence Processing, Object virtue of its “rules and representations” Recognition) !! Representation and Algorithm: "! We can explain behavior (cognitive "! Representations that the system manipulates and how it does it (What types of behavior) by specifying the nature of the representations are used, What types of rules, rules and representations a system What kinds of processes) encodes !! Implementation: "! Physical instantiation (the nature of the actual physical device - e.g., the brain, the computer) 29 Marr, 1982 30 Cognitive Theorizing !! The Brain as the “organ” of the Mind !! Representationalism: Emphasis on Mental Representations !! Functionalism: emergent properties !! Different Representationalist Schools: "! Symbolic (Turing-like, computations) "! Connectionist (“brain-like”, associations) 31