Perfect information games require a decent amount of forethought and planning to play well. Unlike the other game-playing systems DeepMind developed previously, like the chess-winning AlphaZero and StarCraft II-besting AlphaStar, Player of Games can perform well at both perfect information games (e.g., the Chinese board game Go and chess) as well as imperfect information games (e.g., poker). In a continuation of its work, DeepMind has created a system called Player of Games, which the company first revealed in a research paper published on the preprint server this week. In recent decades, games have given rise to the kind of self-learning AI that powers computer vision, self-driving cars, and natural language processing.
This makes them useful benchmarks of AI progress. It’s the lab’s philosophy that games, while lacking an obvious commercial application, are uniquely relevant challenges of cognitive and reasoning capabilities. Missed the GamesBeat Summit excitement? Don't worry! Tune in now to catch all of the live and virtual sessions here.ĭeepMind, the AI lab backed by Google parent company Alphabet, has long invested in game-playing AI systems.
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