MCLQ combines linear-quadratic approximations with Monte Carlo refinement to approximate Nash equilibria for safe robot policies in zero-sum human-robot games.
InInternational Conference on Machine Learning
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Safe Interactions via Monte Carlo Linear-Quadratic Games
MCLQ combines linear-quadratic approximations with Monte Carlo refinement to approximate Nash equilibria for safe robot policies in zero-sum human-robot games.