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Trust-Based Mechanisms for Robust and Efficient Task Allocation in the Presence of Execution Uncertainty

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  • Dash, Rajdeep K

    (School of Electronics and Computer Science,University of Southampton)

  • Giovannucci, Andrea

    (Artificial Intelligence Research Institute, Spanish Council for Scientific Research)

  • Jennings, Nicholas R.

    (School of Electronics and Computer Science,University of Southampton,)

  • Mezzetti, Claudio

    (Department of Economics, University of Warwick)

  • Ramchurn, Sarvapali D.

    (School of Electronics and Computer Science,University of Southampton)

  • Rodriguez-Aguilar, Juan A.

    (Artificial Intelligence Research Institute, Spanish Council for Scientific Research)

Abstract

Vickrey-Clarke-Groves (VCG) mechanisms are often used to allocate tasks to selfish and rational agents. VCG mechanisms are incentive-compatible, direct mechanisms that are efficient (i.e. maximise social utility) and individually rational (i.e. agents prefer to join rather than opt out). However, an important assumption of these mechanisms is that the agents will always successfully complete their allocated tasks. Clearly, this assumption is unrealistic in many real-world applications where agents can, and often do, fail in their endeavours. Moreover, whether an agent is deemed to have failed may be perceived differently by different agents. Such subjective perceptions about an agent’s probability of succeeding at a given task are often captured and reasoned about using the notion of trust. Given this background, in this paper, we investigate the design of novel mechanisms that take into account the trust between agents when allocating tasks. Specifically, we develop a new class of mechanisms, called trust-based mechanisms, that can take into account multiple subjective measures of the probability of an agent succeeding at a given task and produce allocations that maximise social utility, whilst ensuring that no agent obtains a negative utility. We then show that such mechanisms pose a challenging new combinatorial optimisation problem (that is NP-complete), devise a novel representation for solving the problem, and develop an effective integer programming solution (that can solve instances with about 2×105 possible allocations in 40 seconds).

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Bibliographic Info

Paper provided by University of Warwick, Department of Economics in its series The Warwick Economics Research Paper Series (TWERPS) with number 880.

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Length: 37 pages
Date of creation: 2008
Date of revision:
Handle: RePEc:wrk:warwec:880

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  1. Jehiel, Phillipe & Moldovanu, Benny, 1998. "Efficient Design with Interdependent Valuations," Sonderforschungsbereich 504 Publications 98-22, Sonderforschungsbereich 504, Universität Mannheim & Sonderforschungsbereich 504, University of Mannheim.
  2. d'Aspremont, Claude & Gerard-Varet, Louis-Andre, 1979. "Incentives and incomplete information," Journal of Public Economics, Elsevier, vol. 11(1), pages 25-45, February.
  3. Peter Cramton & Yoav Shoham & Richard Steinberg, 2004. "Combinatorial Auctions," Papers of Peter Cramton 04mit, University of Maryland, Department of Economics - Peter Cramton, revised 2004.
  4. Claudio Mezzetti, 2007. "Mechanism Design with Interdependent Valuations: Surplus Extraction," Economic Theory, Springer, vol. 31(3), pages 473-488, June.
  5. Babaioff, Moshe & Feldman, Michal & Nisan, Noam & Winter, Eyal, 2012. "Combinatorial agency," Journal of Economic Theory, Elsevier, vol. 147(3), pages 999-1034.
  6. Claudio Mezzetti, 2004. "Mechanism Design with Interdependent Valuations: Efficiency," Econometrica, Econometric Society, vol. 72(5), pages 1617-1626, 09.
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