Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Genetic programming II: automatic discovery of reusable programs
Genetic programming II: automatic discovery of reusable programs
Evolution of obstacle avoidance behavior: using noise to promote robust solutions
Advances in genetic programming
Advances in genetic programming
Proceedings of the workshop on Computational learning theory and natural learning systems (vol. 2) : intersections between theory and experiment: intersections between theory and experiment
A Distributed Model for Mobile Robot Environment-Learning and Navigation
A Distributed Model for Mobile Robot Environment-Learning and Navigation
Associative model for solving the wall-following problem
MCPR'12 Proceedings of the 4th Mexican conference on Pattern Recognition
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The wall following robot is examined as a potential benchmark problem for applications of genetic programming (GP) to emergent robotic behavior. This paper describes experiments that were performed to characterize the performance, solution space, search space, and robustness using GP with and without automatically defined functions (ADFs). GP with ADFs was unable to significantly outperform GP without ADFs on this problem. A sub-optimal modality was discovered across all four program architectures. Many of the optimal solutions that were discovered tended to limit the number of sensors used for wall-following behavior; some used as few as three sensors. Tests for robustness indicate a "handedness" to the evolved solutions, which does seem to contribute to solution brittleness.