Our bots on Lichess are named maia1, maia5, and maia9, which we trained on human games at Elo rating 1100, 1500, and 1900, respectively.

If you’re curious, you can play against a few versions of Maia on Lichess, the popular open-source online chess platform. The question for AI and its ability to learn is: can AI make the same fine-grained decisions that humans do at a specific skill level? This is a good starting point for aligning AI with human behavior in chess.Įxplore our nine final maia models saved as Leela Chess neural networks, and the code to create more and reproduce our results. The goal for our research is to better bridge the gap between AI and human chess-playing abilities. There’s a lot of work out there that attempts to match AI chess play to varying human skill levels, but the result is often AI that makes decisions and plays moves differently than human players at that skill level. These shifts have created a unique testbed for studying the interactions between humans and AI: formidable AI chess-playing ability combined with a large, growing human interest in the game has resulted in a wide variety of playing styles and player skill levels. The impact of this evolution has been monumental: chess is now seeing record numbers of people playing the game even as AI itself continues to get better at playing. Chess stands as a model system for studying how people can collaborate with AI, or learn from AI, just as chess has served as a leading indicator of many central questions in AI throughout the field’s history.ĪI-powered chess engines have consistently bested human players since 2005, and the chess world has undergone further shifts since then, such as the introduction of the heuristics-based Stockfish engine in 2008 and the deep reinforcement learning-based AlphaZero engine in 2017.

Editor’s note: The section “Modeling individual players’ styles with Maia” has been updated as of July 12, 2021.Īs artificial intelligence continues its rapid progress, equaling or surpassing human performance on benchmarks in an increasing range of tasks, researchers in the field are directing more effort to the interaction between humans and AI in domains where both are active.

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