Evolutionary Action Selection for Gradient-based Policy Learning. (arXiv:2201.04286v4 [cs.NE] UPDATED)

Evolutionary Algorithms (EAs) and Deep Reinforcement Learning (DRL) have
recently been integrated to take the advantage of the both methods for better
exploration and exploitation.The evolutionary part in these hybrid methods
maintains a population of policy networks.However, existing methods focus on
optimizing the parameters of policy network, which is usually high-dimensional
and tricky for EA.In this paper, we shift the target of evolution from
high-dimensional parameter space to low-dimensional action space.We propose
Evolutionary Action Selection-Twin Delayed Deep Deterministic Policy Gradient …

arxiv gradient policy