A model based on genetic algorithm for investigation of the behavior of rats in the elevated plus-maze

Authors:
Ariadne A. Costa;Antonio C. Roque;Silvio Morato;Renato Tinós
Affiliations:
Department of Physics, FFCLRP, University of São Paulo (USP), Ribeirão Preto, S.P., Brazil;Department of Physics, FFCLRP, University of São Paulo (USP), Ribeirão Preto, S.P., Brazil;Department of Psychology, FFCLRP, University of São Paulo (USP), Ribeirão Preto, S.P., Brazil;Department of Computing and Mathematics, FFCLRP, University of São Paulo (USP), Ribeirão Preto, S.P., Brazil
Venue:
IDEAL'12 Proceedings of the 13th international conference on Intelligent Data Engineering and Automated Learning
Year:
2012

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Abstract

In this paper we propose the use of an artificial neural network associated to a genetic algorithm to develop a behavioral model of rats in elevated plus-maze. The main novelty is the fitness function used, which is independent of prior known experimental data. Our results agree with experimental tests, demonstrating that open arms exploration evoke greater avoidance. The perspective of the results are increased by analyzing Markov chains obtained by experiments with real rats and by computational simulations, suggesting that the general fitness function proposed summarizes the main relevant characteristics for the study of the rats behavior in the elevated plus-maze.