Organisation of robot behaviour through genetic learning processes

Abstract

Behaviour-based robotics represents a different approach to modelling the interaction of an autonomous agent with its environment hence providing the basis for the development of cognitive capabilities in artificially intelligent systems. The authors present a machine learning approach based on genetic algorithms and unsupervised reinforcement learning to the generation and organisation of robot behaviour. The implementation of an ethological model of behavioural organisation based on genetics-based machine learning is outlined.<>