Evolution of robotic behaviours using Gene Expression Programming

Genetic Algorithms and Genetic programming have been used extensively in Evolutionary robotics (ER) with the goal of automatic programming of robotic controllers and has shown to be a promising approach. In this paper, we demonstrate the use of Gene Expression Programming, GEP, a newly developed evolutionary algorithm akin to GA and GP, to evolve robotic behaviours. We use the already well known obstacle avoidance behaviour for our initial work. The behaviour can be regarded as emergent when the main aim is to develop a wandering/exploratory behaviour. From our investigations, we show that GEP is able to learn controllers for a number of different environments. Moreover, standard GEP has never been used before in evolving robotic behaviours, however due to its reported good performances in other fields, we feel it has the capability to be used in ER.