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Moshe Tennenholtz

  1. Solving Cooperative Reliability Games.

    Пнд, 02/20/2012 - 15:01 — SomNambul
    Authors: Michal Feldman, Moshe Tennenholtz, Yoram Bachrach, Reshef Meir
    Subjects: Computer Science and Game Theory
    Abstract

    Cooperative games model the allocation of profit from joint actions,
    following considerations such as stability and fairness. We propose the
    reliability extension of such games, where agents may fail to participate in
    the game. In the reliability extension, each agent only "survives" with a
    certain probability, and a coalition's value is the probability that its
    surviving members would be a winning coalition in the base game. We study
    prominent solution concepts in such games, showing how to approximate the
    Shapley value and how to compute the core in games with few agent types.

  2. Signaling Schemes for Revenue Maximization.

    Чт, 02/09/2012 - 15:01 — SomNambul
    Authors: Michal Feldman, Moshe Tennenholtz, Yuval Emek, Iftah Gamzu, Renato Paes Leme
    Subjects: Computer Science and Game Theory
    Abstract

    Signaling is an important topic in the study of asymmetric information in
    economic settings. In particular, the transparency of information available to
    a seller in an auction setting is a question of major interest. We introduce
    the study of signaling when conducting a second price auction of a
    probabilistic good whose actual instantiation is known to the auctioneer but
    not to the bidders. This framework can be used to model impressions selling in
    display advertising. We study the problem of computing a signaling scheme that
    maximizes the auctioneer's revenue in a Bayesian setting.

  3. Approximately Optimal Mechanism Design via Differential Privacy.

    Пнд, 04/19/2010 - 15:02 — SomNambul
    Authors: Moshe Tennenholtz, Kobbi Nissim, Rann Smorodinsky
    Subjects: Computer Science and Game Theory
    Abstract

    We introduce a general technique for obtaining approximately optimal truthful
    mechanisms implementing general social welfare functions without payments. We
    combine a differentially private mechanism, which induces efficiency but does
    not guarantee truthfulness, with a probabilistic mechanism that is truthful yet
    inefficient. The combined mechanism enjoys the best of both worlds -
    truthfulness and efficiency. We demonstrate the applicability of our results
    for addressing open problems in facility location and in the pricing of goods.

  4. Sum of Us: Strategyproof Selection from the Selectors.

    Втр, 10/27/2009 - 16:01 — SomNambul
    Authors: Noga Alon, Felix Fischer, Ariel D. Procaccia, Moshe Tennenholtz
    Subjects: Computer Science and Game Theory
    Abstract

    We consider directed graphs over a set of n agents, where an edge (i,j) is
    taken to mean that agent i supports or trusts agent j. Given such a graph and
    an integer k\leq n, we wish to select a subset of k agents that maximizes the
    sum of indegrees, i.e., a subset of k most popular or most trusted agents. At
    the same time we assume that each individual agent is only interested in being
    selected, and may misreport its outgoing edges to this end.

Math-arch

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