The Representationalist Assumption
Symbol structures are internal representations of external reality, made up of symbols and operated on by psychological processes (inc. rules and search). They're constituent in that their meaning is a function of the meaning of their parts.
Symbol structures are internal representations of external reality. They are made up of symbols, and are operated on by rules, search, and other psychological processes. Symbolic representations of the constituent structure, into the meaning of a given representation is a function of the meaning of its constituent parts.


Notes:

  • Symbol structures in this sense are often referred to as mental representations or classical representations.
  • For more on this classical AI theory of representation, see Newell & Simon (1976), Fodor (1975), and Pylyshyn (1984).
  • Much of the debate  between connectionism and classical AI is focused on the issue of mental representation. One of AI's major charges against connectionism is that connection is networks can't model constituent structure. See the "Can connection is networks exhibit systematiciity?" arguments on Map 5.
Immediately related elementsHow this works
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Artificial Intelligence Â»Artificial Intelligence
Can computers think? [1] Â»Can computers think? [1]
Yes: physical symbol systems can think [3] Â»Yes: physical symbol systems can think [3]
The Representationalist Assumption
The Objectivist account of cognition Â»The Objectivist account of cognition
Front-end Assumption is dubious Â»Front-end Assumption is dubious
The representational tradition is flawed Â»The representational tradition is flawed
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