- author = "Enrique Frias-Martinez and Fernand Gobet",
- title = "Automatic Generation of Cognitive Theories using Genetic Programming",
- journal = "Minds and Machines",
- volume = "17",
- number = "3",
- year = "2007",
- pages = "287--309",
- month = oct,
- address = "Hingham, MA, USA",
- publisher = "Kluwer Academic Publishers",
- keywords = "genetic algorithms, genetic programming, Cognitive neuroscience, Computational neuroscience, Automatic generation of cognitive theories, Delayed-match-to-sample",
- ISSN = "0924-6495",
-
DOI = "
doi:10.1007/s11023-007-9070-6",
- size = "23 pages",
- 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 (GP). 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.",
-
notes = "Artificial intelligence, cognitive memory. Fit both
mean and standard deviation of experimental (people)
results. Lisp. Data from Chao et al. 1999, pictures of
animals and pictures of tools. WSTM. Table 3 putSTM ...
{"}Write the input parameter in STM{"}
Also known as \cite{1298700}",
