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Regret-based Optimization and Preference Elicitation for Stackelberg Security Games with Uncertainty Thanh H. Nguyen1 , Amulya Yadav1 , Bo An2 , Milind Tambe1 , Craig Boutilier3 1 University of Southern California, Los
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Document Date: 2014-05-02 13:24:05


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File Size: 1,21 MB

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Constraint / /

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AUAI Press / Cambridge University Press / Halsted Press / ct Rt Pt / Multiagent Systems / Intel / /

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Canada / /

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University of Southern California / University of Toronto / Nanyang Technological University / /

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δ-optimal solution / expected utilities / maximin-based robust solutions / minimax regret solution / game-theoretic solutions / feasible solution / binary search / local search / binary-search termination threshold / final solution / bCISM algorithm / online appendix / e - commerce / binary search decision problem / binary-search based algorithm / /

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Cambridge University / University of Southern California / Los Angeles / Artificial Copyright Intelligence / Nanyang Technological University / Singapore / Association for the Advancement / University of Toronto / /

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Payoff Uncertainty / Max Regret / Van Roy / Pt / /

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driver / Rt / reward Rt / /

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Southern California / California / /

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Journal of Economic Theory / /

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Southern California / /

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three MR algorithms / binary-search based algorithm / Approximate Linearization Algorithm / bCISM algorithm / artificial intelligence / ALARM algorithm / MMR algorithms Evaluating MMR Algorithms / /

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