AI RESEARCH
FAIRGAME: a Framework for AI Agents Bias Recognition using Game Theory
arXiv CS.AI
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ArXi:2504.14325v5 Announce Type: replace Letting AI agents interact in multi-agent applications adds a layer of complexity to the interpretability and prediction of AI outcomes, with profound implications for their trustworthy adoption in research and society. Game theory offers powerful models to capture and interpret strategic interaction among agents, but requires the of reproducible, standardized and user-friendly IT frameworks to enable comparison and interpretation of results. To this end, we present FAIRGAME, a Framework for AI Agents Bias Recognition using Game Theory.