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News/Learning in Matching Games with Bandit Feedback
arxiv
PublishedJune 17, 2026 at 4:00 AM
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Learning in Matching Games with Bandit Feedback

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arXiv:2506.03802v2 Announce Type: replace Abstract: We introduce a learning problem in a generalized two-sided matching market, where agents select actions to interact with their match. Specifically, we consider a setting in which matched agents engage in zero-sum games with initially unknown payoff

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Read original ↗All from arxiv →
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#machine-learning#game-theory#algorithm#research

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