This study addresses the limitations of traditional multi-armed bandit algorithms by introducing a new algorithm, DUSA, which effectively utilizes structural information to minimize regret. DUSA aligns with the information-theoretic lower bound and is computationally viable, offering minimal regret for both known and new structured bandits.
👤 Negin Golrezaei Associate Professor, MIT Sloan School of Management
This study addresses the limitations of traditional multi-armed bandit algorithms by introducing a new algorithm, DUSA, which effectively utilizes structural information to minimize regret. DUSA aligns with the information-theoretic lower bound and is computationally viable, offering minimal regret for both known and new structured bandits.
👤 Negin Golrezaei Associate Professor, MIT Sloan School of Management
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