Representation and rule-instantiation in connectionist systems
David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Ezio Di Nucci
Jonathan Jenkins Ichikawa
Jack Alan Reynolds
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In Terence E. Horgan & John L. Tienson (eds.), Connectionism and the Philosophy of Mind. Kluwer (1991)
There is disagreement over the notion of representation in cognitive science. Many investigators equate representations with symbols, that is, with syntactically defined elements in an internal symbol system. In recent years there have been two challenges to this orthodoxy. First, a number of philosophers, including many outside the symbolist orthodoxy, have argued that "representation" should be understood in its classical sense, as denoting a "stands for" relation between representation and represented. Second, there has been a growing challenge to orthodoxy under the banner of connectionism. Although this connectionist challenge has evoked emotionally-charged rebukes from the symbolist camp, connectionists as a group have not articulated a conception of representation to replace the symbolist view. Nonetheless, most agree on the need for a nonsymbolic notion of representation. This paper advances a "stands for" sense of representation as primary by incorporating it into a general approach to cognitive science consonant with the connectionism. The idea is to marry connectionism to a particular version of functionalism, viz., one that builds its notion of "function" on the similarity between functional analysis in biology and in psychology. It builds on my earlier work adapting and revising Marr's tri-level approach to cognition. My proposal frees Marr's analysis from its moorings in the orthodox symbolic view of representation and allies it with a notion of functional analysis akin to that proposed by Cummins, developed further by Haugeland, and invoked by Millikan and Dretske. Unlike these authors, however, I do not wed representation to a general belief-desire analysis of behavior. Rather, I follow what I take to be the lesson of psychological practice, according to which the investigator does not seek to explain behavior in general but seeks to analyze the cognitive capacities that underlie behavior, such as vision, memory, learning, and linguistic capacities. Accordingly, ascriptions of representational content are made not by working back from belief-desire ascriptions, but in the context of forming psychological models to account for specific cognitive capacities. Because conceptions of representation in cognitive science typically are embedded in a general approach to the study of cognition, arguments for the comparative plausibility of a particular conception of representation must scout these larger frameworks. I therefore begin by characterizing the interlocking set of assumptions that gave life to the orthodox symbolist approach, paying special attention to the complementarity between representation and process that naturally arises from those assumptions. I then consider two versions of an alternative approach to representation: Dretske's and my own. Finally, I urge the merits of the "cognitive capacities" over the "belief-desire" approach to the subject-matter of cognitive science.
|Keywords||Connectionism Symbol systems Representation Functional analysis Dretske, F Fodor, J Marr, D Belief-desire analysis of behavior|
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Citations of this work BETA
L. Shastri & V. Ajjanagadde (1993). From Simple Associations to Systematic Reasoning: A Connectionist Representation of Rules, Variables, and Dynamic Binding Using Temporal Synchrony. Behavioral and Brain Sciences 16 (3):417-51.
William Ramsey (1997). Do Connectionist Representations Earn Their Explanatory Keep? Mind and Language 12 (1):34-66.
John E. Hummel & Keith J. Holyoak (1993). Distributing Structure Over Time. Behavioral and Brain Sciences 16 (3):464.
Garrison W. Cottrell (1993). From Symbols to Neurons: Are We There Yet? Behavioral and Brain Sciences 16 (3):454.
Mike Oaksford & Mike Malloch (1993). Computational and Biological Constraints in the Psychology of Reasoning. Behavioral and Brain Sciences 16 (3):468.
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