On-line evolution of robot controllers by an encapsulated evolution strategy

This paper describes and experimentally evaluates the viability of the (μ + 1) ON-LINE evolutionary algorithm for on-line adaptation of robot controllers. Secondly, it explores the parameter space for this algorithm and identifies four important parameters: the population size μ, the re-evaluation rate ρ, the mutation step-size σ and the controller evaluation period τ. Subsequently, it investigates their influence on controller performance, stability of behaviour and speed of adaptation. The results indicate that the encapsulated on-line evolutionary approach is a viable one and merits further research. In agreement with existing research, the mutation step-size σ proves to be of overriding importance to finding good solutions. Specific to on-line evolution, the results show that longer evaluation times greatly benefit the quality of controllers as well as stability of behaviour and speed of adaptation.