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Ivan Tanev 《Genetic Programming and Evolvable Machines》2007,8(1):39-59
In this work we propose an approach for incorporating learning probabilistic context-sensitive grammar (LPCSG) in genetic
programming (GP), employed for evolution and adaptation of locomotion gaits of a simulated snake-like robot (Snakebot). Our
approach is derived from the original context-free grammar which usually expresses the syntax of genetic programs in canonical
GP. Empirically obtained results verify that employing LPCSG contributes to the improvement of computational effort of both
(i) the evolution of the fastest possible locomotion gaits for various fitness conditions and (ii) adaptation of these locomotion
gaits to challenging environment and degraded mechanical abilities of the Snakebot. 相似文献
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