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  1. Task-dependent constraints on perceptual architectures.Roy Eagleson - 1990 - Behavioral and Brain Sciences 13 (3):447-448.
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  • Goals, analogy, and the social constraints of scientific discovery.Kevin Dunbar & Lisa M. Baker - 1994 - Behavioral and Brain Sciences 17 (3):538-539.
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  • Computation: Part of the problem of creativity.Merlin Donald - 1994 - Behavioral and Brain Sciences 17 (3):537-538.
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  • Computation, complexity, and systems in nature.Bradley W. Dickinson - 1990 - Behavioral and Brain Sciences 13 (3):447-447.
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  • Complexity at the neuronal level.Robert Desimone - 1990 - Behavioral and Brain Sciences 13 (3):446-446.
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  • Creativity, combination, and cognition.Terry Dartnall - 1994 - Behavioral and Brain Sciences 17 (3):537-537.
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  • The theory and practice of attention.Kyle R. Cave - 1990 - Behavioral and Brain Sciences 13 (3):445-446.
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  • On doing the impossible.Robert L. Campbell - 1994 - Behavioral and Brain Sciences 17 (3):535-537.
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  • Analogy programs and creativity.Bruce D. Burns - 1994 - Behavioral and Brain Sciences 17 (3):535-535.
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  • What is the difference between real creativity and mere novelty?Alan Bundy - 1994 - Behavioral and Brain Sciences 17 (3):533-534.
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  • Lady Lovelace had it right: Computers originate nothing.Selmer Bringsjord - 1994 - Behavioral and Brain Sciences 17 (3):532-533.
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  • Précis of The creative mind: Myths and mechanisms.Margaret A. Boden - 1994 - Behavioral and Brain Sciences 17 (3):519-531.
    What is creativity? One new idea may be creative, whereas another is merely new: What's the difference? And how is creativity possible? These questions about human creativity can be answered, at least in outline, using computational concepts. There are two broad types of creativity, improbabilist and impossibilist. Improbabilist creativity involves novel combinations of familiar ideas. A deeper type involves METCS: the mapping, exploration, and transformation of conceptual spaces. It is impossibilist, in that ideas may be generated which – with respect (...)
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  • Creativity: A framework for research.Margaret A. Boden - 1994 - Behavioral and Brain Sciences 17 (3):558-570.
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  • Influence-based model decomposition for reasoning about spatially distributed physical systems.Chris Bailey-Kellogg & Feng Zhao - 2001 - Artificial Intelligence 130 (2):125-166.
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  • Can artificial intelligence explain age changes in literary creativity?Carolyn Adams-Price - 1994 - Behavioral and Brain Sciences 17 (3):532-532.
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  • Mental imagery.Nigel J. T. Thomas - 2001 - Stanford Encyclopedia of Philosophy.
    Mental imagery (varieties of which are sometimes colloquially refered to as “visualizing,” “seeing in the mind's eye,” “hearing in the head,” “imagining the feel of,” etc.) is quasi-perceptual experience; it resembles perceptual experience, but occurs in the absence of the appropriate external stimuli. It is also generally understood to bear intentionality (i.e., mental images are always images of something or other), and thereby to function as a form of mental representation. Traditionally, visual mental imagery, the most discussed variety, was thought (...)
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  • Coherence and analogy articles.Paul Thagard - manuscript
    Barnes, A. and P. Thagard Empathy and analogy. Dialogue: Canadian Philosophical Review, 36: 705-720. HTML Croft, D., & Thagard, P.. Dynamic imagery: A computational model of motion and visual analogy. In L. Magnani and N. Nersessian, Model-based reasoning: Science, technology, values. New York: Kluwer/Plenum, 259-274. PDF only. HTML description of program and code for DIVA.
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