2008 | OriginalPaper | Buchkapitel
Evolving Vision Controllers with a Two-Phase Genetic Programming System Using Imitation
verfasst von : Renaud Barate, Antoine Manzanera
Erschienen in: From Animals to Animats 10
Verlag: Springer Berlin Heidelberg
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We present a system that automatically selects and parameterizes a vision based obstacle avoidance method adapted to a given visual context. This system uses genetic programming and a robotic simulation to evaluate the candidate algorithms. As the number of evaluations is restricted, we introduce a novel method using imitation to guide the evolution toward promising solutions. We show that for this problem, our two-phase evolution process performs better than other techniques.