Evolutionary Action Selection for Gradient-based Policy Learning. (arXiv:2201.04286v1 [cs.NE])

Evolutionary Algorithms (EAs) and Deep Reinforcement Learning (DRL) have
recently been combined to integrate the advantages of the two solutions for
better policy learning. However, in existing hybrid methods, EA is used to
directly train the policy network, which will lead to sample inefficiency and
unpredictable impact on the policy performance. To better integrate these two
approaches and avoid the drawbacks caused by the introduction of EA, we devote
ourselves to devising a more efficient and reasonable method of combining …

arxiv gradient learning policy