Building AI that can master complex cooperative games with hidden information

We've built an AI bot that achieves state-of-the-art results in Hanabi, a collaborative card game that has been cited as a benchmark game for AI research because it features both cooperative gameplay and imperfect information. Our bot outperforms previous AI algorithms at Hanabi by using real-time search to fine-tune its decisions during gameplay. It's the first bot to exceed elite human performance in the game, as judged by experienced players who have evaluated it. Researchers have found it challenging to apply search beyond perfect-information games like chess and Go. Our success with Hanabi suggests search can improve more AI systems and eventually help build AI that learns to master complex cooperative tasks in real-world settings.