Algebraic Mind: Integrating Connectionism and Cognitive by Gary F. Marcus

By Gary F. Marcus

An try and combine theories approximately how the brain works, person who says that the brain is a computer-like manipulator of symbols, and one other that claims that the brain is a big community of neurons operating jointly in parallel.

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Extra info for Algebraic Mind: Integrating Connectionism and Cognitive Science

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5 Symbols, Symbol-Manipulators, and Multilayer Perceptrons First, though, before we examine what I think truly distinguishes multilayer perceptrons from symbol-manipulation, it is important to clear up a red herring. A number of people seem to think that a key difference between multilayer perceptrons and symbol-manipulators is that the latter make use of symbols but the former do not. For example, Paul Churchland (1990, p. 227) seems to suggest this when he writes An individual’s overall-theory-of-the-world, we might venture, is not a large collection or a long list of stored symbolic items.

A better understanding of that relationship will help clarify whether the mind does in fact make use of operations over variables and also clarify how such operations can be implemented in a neural substrate. To make the strongest possible case that the mind does in fact implement operations over variables, I focus on what I call universally quantified one-to-one mappings (UQOTOM). The terms universally quantified and one-to-one come from logic and mathematics. A function is universally quantified when it applies to all instances in its domain.

The actual examples he gives of Multilayer Perceptrons 33 representations are invariably grounded in lower-level features that are themselves context-independent. For example, cup of coffee is grounded in context-independent features like +porcelain-curved-surface. Hence the subsymbol-symbol distinction seems to be a distinction without a difference. Also often mentioned in these sorts of discussions is the distributedversus-localist distinction. A great many people have made it seem that multilayer perceptrons are special because they make use of distributed representations.

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