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

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... sults 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.