Learning Montezuma’s Revenge from a single demonstration

OpenAI Blog · 8 years ago

An AI agent learned to play Montezuma's Revenge from a single human demonstration, achieving a score of 74,500. The agent was trained by replaying games from states extracted from that single demonstration and optimizing performance using PPO reinforcement learning. This outperforms previous methods that required multiple demonstrations or other learning approaches to master the same game.