When Does Neuroevolution Outcompete Reinforcement Learning in Transfer Learning Tasks?

This paper explores the transfer learning potential of neuroevolution (NE), comparing its performance to reinforcement learning (RL) in tasks requiring skill transfer across increasing complexities. Using new benchmarks, the study finds that NE methods often outperform RL baselines, highlighting NE's promise for developing more adaptable artificial agents, though scaling remains a challenge.