David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
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Behavioral and Brain Sciences 1 (1):98-128 (1978)
It is argued that the traditional distinction between artificial intelligence and cognitive simulation amounts to little more than a difference in style of research - a different ordering in goal priorities and different methodological allegiances. Both enterprises are constrained by empirical considerations and both are directed at understanding classes of tasks that are defined by essentially psychological criteria. Because of the different ordering of priorities, however, they occasionally take somewhat different stands on such issues as the power/generality trade-off and on the relevance of the sort of data collected in experimental psychology laboratories
|Keywords||artificial intelligence cognition cognitive science methodology empirical constraints computer simulation|
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References found in this work BETA
Jerry A. Fodor (1975). The Language of Thought. Harvard University Press.
Nelson Goodman (1983). Fact, Fiction, and Forecast. Harvard University Press.
John Haugeland (1979). Author's Response. Behavioral and Brain Sciences 2 (4):634-635.
C. Wade Savage & C. Anthony Anderson (eds.) (1989). Minesota Studies in the Philosophy of Science. University of Minnesota Press.
Citations of this work BETA
David J. Buller (1993). Confirmation and the Computational Paradigm (Or: Why Do You Think They Call Itartificial Intelligence?). [REVIEW] Minds and Machines 3 (2):155-181.
Annette Karmiloff-Smith (1986). From Meta-Processes to Conscious Access: Evidence From Children's Metalinguistic and Repair Data. Cognition 23 (2):95-147.
George A. Miller (1981). Trends and Debates in Cognitive Psychology. Cognition 10 (1-3):215-225.
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