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  • Publication . Article . Preprint . 2013 . Embargo End Date: 01 Jan 2013
    Open Access
    Authors: 
    Zoghi, M.; Whiteson, S.; Munos, R.; de Rijke, M.;
    Publisher: arXiv
    Project: NWO | SPuDisc: Searching Public... (2300176811), NWO | Semantic Search in E-Disc... (2300168486), NWO | Digging archaeology data:... (2300186891), NWO | Modeling and Learning fro... (2300171779), EC | COMPLACS (270327), EC | LIMOSINE (288024), NWO | Building Rich Links to En... (2300153702)

    This paper proposes a new method for the K-armed dueling bandit problem, a variation on the regular K-armed bandit problem that offers only relative feedback about pairs of arms. Our approach extends the Upper Confidence Bound algorithm to the relative setting by using estimates of the pairwise probabilities to select a promising arm and applying Upper Confidence Bound with the winner as a benchmark. We prove a finite-time regret bound of order O(log t). In addition, our empirical results using real data from an information retrieval application show that it greatly outperforms the state of the art. Comment: 13 pages, 6 figures