Overcoming Free Riding in Multi-Party Computations

Authors Rann Smordinsky, Moshe Tennenholtz

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Rann Smordinsky
Moshe Tennenholtz

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Rann Smordinsky and Moshe Tennenholtz. Overcoming Free Riding in Multi-Party Computations. In Computing and Markets. Dagstuhl Seminar Proceedings, Volume 5011, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2005)


This paper addresses the question of multi party computation in a model with asymmetric information. Each agent has a private value (secret), but in contrast to standard models, the agent incurs a cost when retrieving the secret. There is a social choice function the agents would like to compute and implement. All agents would like to perform a joint computation, which input is their vector of secrets. However, agents would like to free-ride on others contribution. A mechanism which elicits players secrets and performs the desired computation defines a game. A mechanism is `appropriate if it (weakly) implements the social choice function for all secret vectors. namely, if there exists an equilibrium in which it is able to elicit (sufficiently many) agents secrets and perform the computation, for all possible secret vectors. We show that `appropriate mechanisms approach agents sequentially and that they have low communication complexity.
  • compact representation of games
  • congestion games
  • local-effect games
  • action-graph gamescomputational markets; auctions; bidding strategiesNegotiatio


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