Abstract
In this paper, we compare the performance of hierarchical GP methods (Automatically Defined Functions, Module Acquisition, Adaptive Representation through Learning) with the canonical GP Implementation and with a linear genome GP system in the domain of evolving robotic controllers for a simulated Khepera miniature robot. We successfully evolve robotic controllers to accomplish obstacle avoidance, wall following, and light avoidance tasks.
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Pilat, M.L., Oppacher, F. (2004). Robotic Control Using Hierarchical Genetic Programming. In: Deb, K. (eds) Genetic and Evolutionary Computation – GECCO 2004. GECCO 2004. Lecture Notes in Computer Science, vol 3103. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24855-2_72
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DOI: https://doi.org/10.1007/978-3-540-24855-2_72
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22343-6
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