Evolution strategies as a scalable alternative to reinforcement learning

Researchers have found that evolution strategies (ES), a decades-old optimization technique, can match the performance of modern reinforcement learning methods on standard benchmarks like Atari and MuJoCo. This discovery suggests ES could serve as a more scalable alternative to traditional RL approaches while avoiding many of RL's practical limitations.