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Title: Automatic Generation of Cognitive Theories using Genetic Programming
Authors: Frias-Martinez, E
Gobet, F
Keywords: Cognitive Neuroscience;Computational Neuroscience;Theory generation;Theory building;Genetic Programming;evolutionary computation;Delayed-Match-To-Sample;scientific discovery;search;fitness function;tree representation;modularity;hierarchy;bloating;cognitive architecture;memory
Issue Date: 2007
Publisher: Springer Verlag
Citation: Frias-Martinez , E., & Gobet, F. (in press). Automatic generation of cognitive theories using genetic programming. Minds & Machines.
Abstract: Cognitive neuroscience is the branch of neuroscience that studies the neural mechanisms underpinning cognition and develops theories explaining them. Within cognitive neuroscience, computational neuroscience focuses on modeling behavior, using theories expressed as computer programs. Up to now, computational theories have been formulated by neuroscientists. In this paper, we present a new approach to theory development in neuroscience: the automatic generation and testing of cognitive theories using genetic programming. Our approach evolves from experimental data cognitive theories that explain “the mental program” that subjects use to solve a specific task. As an example, we have focused on a typical neuroscience experiment, the delayed-match-to-sample (DMTS) task. The main goal of our approach is to develop a tool that neuroscientists can use to develop better cognitive theories.
Appears in Collections:Psychology
Dept of Life Sciences Research Papers

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