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This paper presents a method for the biped dynamic walking and balance control using reinforcement learning, which learns dynamic walking without a priori knowledge about the dynamic model. The learning architecture developed is aimed to solve complex control problems in robotic actuation control by mapping the action space from a discretized domain to a continuous one. It employs the discrete actions...
In this paper, an evolutionary algorithm inspired by biological deoxyribonucleic acid (DNA) computing is proposed to perform the task of optimization. As a novel branch of computational intelligence, DNA computing has the strong computing and proliferating capability to in DNA strands by DNA encoding and matching in the molecule layer. However, it is difficult to apply DNA computing to search processing...
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