Use of Evolutionary Robots as an Auxiliary Tool for Developing Behavioral Models of Rats in an Elevated Plus-Maze

This work proposes the use of evolutionary robots as an auxiliary tool for the development of models to describe rats´ behavior. Evolutionary robots can be useful to test hypothesis and models of behavior, what is demonstrated here in experiments where a mobile robot is trained to reproduce the behavior of the rat in an elevated plus-maze (EPM). A recurrent Elman multilayer perceptron is used to control the robot. Due to the impossibility of knowing each desired output of the neural network, the weight optimization is made by a genetic algorithm. In this way, each individual of the genetic algorithm represents a set of weights of the neural network. Experiments where the fitness of each individual was computed based on the difference between the trajectories of the evolutionary robot on a EPM replica and of the rats behavior on a real EPM are presented.