Covariance matrix adaptation evolution strategy based on correlated evolution paths with application to reinforcement learning
Abstract: Highlights•A correlated evolution path CMAES algorithm is proposed for optimization.•The proposed algorithm is evaluated on IEEE CEC 2014 Benchmark.•The proposed algorithm is applied in optimal policy search on RL tasks.•Comparative performance is demonstrated with other start-of-the-art algorithms.
External IDs:dblp:journals/eswa/AjaniKM24
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