Bridging Evolutionary Algorithms and Reinforcement Learning: A Comprehensive Survey

arXiv:2401.11963v2 Announce Type: replace-cross
Abstract: Evolutionary Reinforcement Learning (ERL), which integrates Evolutionary Algorithms (EAs) and Reinforcement Learning (RL) for optimization, has demonstrated remarkable performance advancements. By fusing the strengths of both approaches, ERL has emerged as a promising research direction. This survey offers a comprehensive overview of the diverse research branches in ERL. Specifically, we systematically summarize recent advancements in relevant algorithms and identify three primary research directions: EA-assisted optimization of RL, RL-assisted optimization of EA, and synergistic optimization of …

algorithms arxiv cs.ai cs.lg cs.ne evolutionary algorithms reinforcement reinforcement learning survey type