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Article de revue:
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Clé de citation BibTeX: Chalmers1992
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Chalmers, D. J., French, R. M., & Hofstadter, D. R. (1992). High-level perception, representation, and analogy:a critique of artificial intelligence methodology. Journal of Experimental and Theoretical Artificial Intellige, 4(3), pp. 185–211.
Ajoutée par: Sterenn Audo 2008-02-06 16:06:37
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Catégories: Analogie, Full text
Auteurs: Chalmers, French, Hofstadter
Collection: Journal of Experimental and Theoretical Artificial Intellige
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Nombre de vues: 274
Popularité: 25%
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Résumé
High-level perception - the process of
making sense of complex data at an abstract,
conceptual levelCis fundamental to human
cognition.Through high-level perception,
chaotic environmental stimuli are organized
into the mental representations that are used
throughout cognitive processing.Much work
in traditional artificial intelligence has ignored
the process of high-level perception,
by starting with hand-coded representations.
In this paper, we argue that this dismissal of
perceptual processes leads to distorted models
of human cognition.We examine some
existing artificial-intelligence modelsCnotably
BACON, a model of scientific discovery,
and the Structure-Mapping Engine, a
model of analogical thoughtCand argue that
these are flawed precisely because they
downplay the role of high-level perception.
Further, we argue that perceptual processes
cannot be separated from other cognitive
processes even in principle, and therefore
that traditional artificial-intelligence models
cannot be defended by supposing the existence
of a "representation module" that supplies
representations ready-made.Finally, we
describe a model of high-level perception and
analogical thought in which perceptual processing
is integrated with analogical mapping,
leading to the flexible build-up of representations
appropriate to a given context.
Ajoutée par: Sterenn Audo
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Idées
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Ajoutée par: Sterenn Audo
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