Connectionism and novel combinations of skills: Implications for cognitive architecture [Book Review]
David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
Learn more about PhilPapers
Minds and Machines 9 (2):197-221 (1999)
In the late 1980s, there were many who heralded the emergence of connectionism as a new paradigm – one which would eventually displace the classically symbolic methods then dominant in AI and Cognitive Science. At present, there remain influential connectionists who continue to defend connectionism as a more realistic paradigm for modeling cognition, at all levels of abstraction, than the classical methods of AI. Not infrequently, one encounters arguments along these lines: given what we know about neurophysiology, it is just not plausible to suppose that our brains are digital computers. Thus, they could not support a classical architecture. I argue here for a middle ground between connectionism and classicism. I assume, for argument's sake, that some form(s) of connectionism can provide reasonably approximate models – at least for lower-level cognitive processes. Given this assumption, I argue on theoretical and empirical grounds that most human mental skills must reside in separate connectionist modules or sub-networks. Ultimately, it is argued that the basic tenets of connectionism, in conjunction with the fact that humans often employ novel combinations of skill modules in rule following and problem solving, lead to the plausible conclusion that, in certain domains, high level cognition requires some form of classical architecture. During the course of argument, it emerges that only an architecture with classical structure could support the novel patterns of information flow and interaction that would exist among the relevant set of modules. Such a classical architecture might very well reside in the abstract levels of a hybrid system whose lower-level modules are purely connectionist
|Keywords||Architecture Artificial Intelligence Connectionism Module Science|
|Categories||categorize this paper)|
Setup an account with your affiliations in order to access resources via your University's proxy server
Configure custom proxy (use this if your affiliation does not provide a proxy)
|Through your library|
References found in this work BETA
No references found.
Citations of this work BETA
Derek C. Penn, Keith J. Holyoak & Daniel J. Povinelli (2008). Darwin's Triumph: Explaining the Uniqueness of the Human Mind Without a Deus Ex Machina. Behavioral and Brain Sciences 31 (2):153-178.
Similar books and articles
William P. Bechtel (1994). Levels of Description and Explanation in Cognitive Science. Minds and Machines 4 (1):1-25.
Michael V. Antony (1991). Fodor and Pylyshyn on Connectionism. Minds and Machines 1 (3):321-41.
Jerry A. Fodor & Zenon W. Pylyshyn (1988). Connectionism and Cognitive Architecture. Cognition 28 (1-2):3-71.
Joseph L. H. Cruz (1998). Mindreading: Mental State Ascription and Cognitive Architecture. Mind and Language 13 (3):323-340.
James W. Garson (1994). Cognition Without Classical Architecture. Synthese 100 (2):291-306.
Marcello Guarini (1996). Tensor Products and Split-Level Architecture: Foundational Issues in the Classicism-Connectionism Debate. Philosophy of Science 63 (3):S239-S247.
Paul Smolensky (1995). Constituent Structure and Explanation in an Integrated Connectionist/Symbolic Cognitive Architecture. In C. Macdonald (ed.), Connectionism: Debates on Psychological Explanation. Blackwell.
Keith Butler (1991). Towards a Connectionist Cognitive Architecture. Mind and Language 6 (3):252-72.
William Ramsey, Stephen P. Stich & D. M. Rumelhart (eds.) (1991). Philosophy and Connectionist Theory. Lawrence Erlbaum.
Brian P. McLaughlin & F. Warfield (1994). The Allure of Connectionism Reexamined. Synthese 101 (3):365-400.
Added to index2009-01-28
Total downloads10 ( #161,211 of 1,413,333 )
Recent downloads (6 months)1 ( #154,079 of 1,413,333 )
How can I increase my downloads?