On the design of neuro-controllers for individual and social learning behaviour in autonomous robots: an evolutionary approach

In Biology/Psychology the capability of natural organisms to learn from the observation/interaction with conspecifics is referred to as social learning. Roboticists have recently developed an interest on social learning, since it might represent an effective strategy to enhance the adaptivity of a team of autonomous robots. In this study, we show that a methodological approach based on artifcial neural networks shaped by evolutionary computation techniques can be successfully employed to synthesise individual and social learning mechanisms for robots required to learn a desired action (i.e., phototaxis or antiphototaxis).