Fodor, J., & Pylyshyn, Z. (1988). Connectionism and cognitive architercture: A critical analysis. Cognition, 28, 3-71. Home/Search Document Not in Database Summary Related Articles Check |
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Probing and Prediction: A Pragmatic View of Cognitive Modeling - French, Cleeremans (Correct)
....it. Existence proofs fall into this category. Three examples from connectionist modeling will serve to illustrate this point. One of the strong claims of traditional artificial intelligence (AI) has always been that transformational grammars can only be modeled in rule based symbolic systems (Fodor Pylyshyn, 1988). Chalmers (1990) however, showed how a RAAM connectionist architecture (Pollack, 1989) could also produce active to passive transformations. RAAM 9 networks are a variety of recurrent connectionist networks that are capable of learning how to process hierarchical structures. Because RAAM ....
Fodor, J., & Pylyshyn, Z. (1988). Connectionism and cognitive architercture: A critical analysis. Cognition, 28, 3-71.
Principles for Implicit Learning - Cleeremans (1996) (3 citations) (Correct)
....learning. 2. The classical metaphor of cognition The central argument of this chapter is that implicit learning is problematic only because the traditional framework within which we think about cognition is flawed. This classical metaphor of cognition (e.g. Newell Simon, 1972; Fodor, 1983; Fodor Pylyshyn, 1988) goes roughly like this: There is a central processor that fetches or stores information in knowledge bases, and processes it. The processor interacts with the world through input output systems. These subsystems are modular, that is, autonomous and informationally encapsulated. Knowledge (either ....
Fodor, J., & Pylyshyn, Z. (1988). Connectionism and cognitive architercture: A critical analysis. Cognition, 28, 3-71.
From Chicken Squawking To Cognition: Levels Of Description.. - Cleeremans, French (1996) (Correct)
....produce it. Existence proofs fall into the same category. Three examples from connectionist modeling will serve to illustrate this point. A strong claim of traditional artificial intelligence (AI) has always been that transformational grammars can only be modeled in rule based symbolic systems (Fodor Pylyshyn, 1988). Chalmers (1990) however, showed how a recursive auto associative memory (raam) connectionist architecture (Pollack, 1989) can also produce active to passive transformations. raam networks can learn how to process hierarchical structures (that describe linguistic expressions or decision trees, ....
Fodor, J., & Pylyshyn, Z. (1988). Connectionism and cognitive architercture: A critical analysis. Cognition, 28, 3-71.
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