Particle swarm optimization for unsupervised robotic learning
作者： J. Pugh , A. Martinoli , Yizhen Zhang
关键词:
摘要: We explore using particle swarm optimization on problems with noisy performance evaluation, focusing unsupervised robotic learning. adapt a technique of overcoming noise used in genetic algorithms for use optimization, and evaluate the both original algorithm noise-resistant method several numerical added noise, as well learning obstacle avoidance one or more robots.
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