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Found 5 papers, 4 papers with code
Designing Skill-Compatible AI: Methodologies and Frameworks in Chess
Traditional chess engines designed to output near-optimal moves prove to be inadequate partners when paired with engines of various lower skill levels in this domain, as they are not designed to consider the presence of other agents.
Detecting Individual Decision-Making Style: Exploring Behavioral Stylometry in Chess
We present a transformer-based approach to behavioral stylometry in the context of chess, where one attempts to identify the player who played a set of games.
Mimetic Models: Ethical Implications of AI that Acts Like You
An emerging theme in artificial intelligence research is the creation of models to simulate the decisions and behavior of specific people, in domains including game-playing, text generation, and artistic expression.
Learning Models of Individual Behavior in Chess
AI systems that can capture human-like behavior are becoming increasingly useful in situations where humans may want to learn from these systems, collaborate with them, or engage with them as partners for an extended duration.
Aligning Superhuman AI with Human Behavior: Chess as a Model System
We develop and introduce Maia, a customized version of Alpha-Zero trained on human chess games, that predicts human moves at a much higher accuracy than existing engines, and can achieve maximum accuracy when predicting decisions made by players at a specific skill level in a tuneable way.
