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Trust-based mechanisms for robust and efficient task allocation in the presence of execution uncertainty

Trust-based mechanisms for robust and efficient task allocation in the presence of execution uncertainty
Trust-based mechanisms for robust and efficient task allocation in the presence of execution uncertainty
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 2x105 possible allocations in 40 seconds).
mechanism design, trust, optimisation, uncertainty
1-41
Ramchurn, Sarvapali D.
1d62ae2a-a498-444e-912d-a6082d3aaea3
Mezzetti, Claudio
24788257-35c6-40af-8fe5-7978d8804f16
Giovannucci, Andrea
710ddc7b-0664-44f6-bf17-85a210a22239
Rodriguez, Juan A.
bc186c00-7630-4628-8841-585526624e8a
Dash, Rajdeep K.
589f704a-00dd-4921-b4f4-e47362cc552f
Jennings, Nicholas R.
ab3d94cc-247c-4545-9d1e-65873d6cdb30
Ramchurn, Sarvapali D.
1d62ae2a-a498-444e-912d-a6082d3aaea3
Mezzetti, Claudio
24788257-35c6-40af-8fe5-7978d8804f16
Giovannucci, Andrea
710ddc7b-0664-44f6-bf17-85a210a22239
Rodriguez, Juan A.
bc186c00-7630-4628-8841-585526624e8a
Dash, Rajdeep K.
589f704a-00dd-4921-b4f4-e47362cc552f
Jennings, Nicholas R.
ab3d94cc-247c-4545-9d1e-65873d6cdb30

Ramchurn, Sarvapali D., Mezzetti, Claudio, Giovannucci, Andrea, Rodriguez, Juan A., Dash, Rajdeep K. and Jennings, Nicholas R. (2009) Trust-based mechanisms for robust and efficient task allocation in the presence of execution uncertainty. Journal of Artificial Intelligence Research, 35, 1-41. (doi:10.1613/jair.2751).

Record type: Article

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 2x105 possible allocations in 40 seconds).

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Published date: 3 June 2009
Keywords: mechanism design, trust, optimisation, uncertainty
Organisations: Agents, Interactions & Complexity

Identifiers

Local EPrints ID: 267288
URI: http://eprints.soton.ac.uk/id/eprint/267288
PURE UUID: 3ac91bb1-5d2c-4bef-b442-2e44098cf2f9
ORCID for Sarvapali D. Ramchurn: ORCID iD orcid.org/0000-0001-9686-4302

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Date deposited: 22 Apr 2009 08:42
Last modified: 26 Nov 2019 01:46

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