Efficient Metadeliberation Auctions
MetadataShow full item record
CitationCavallo, Ruggiero and David C. Parkes. 2008. Efficient metadeliberation auctions. In Proceedings of the Twenty-third AAAI Conference on Artificial Intelligence and the Twentieth Innovative Applications of Artificial Intelligence Conference: July 13-17, 2008, Chicago, Illinois, ed. American Association for Artificial Intelligence, 50-56. Menlo Park, Calif.: AAAI Press.
AbstractImagine a resource allocation scenario in which the interested parties can, at a cost, individually research ways of using the resource to be allocated, potentially increasing the value they would achieve from obtaining it. Each agent has a private model of its research process and obtains a private realization of its improvement in value, if any. From a social perspective it is optimal to coordinate research in a way that strikes the right tradeoff between value and cost, ultimately allocating the resource to one party- thus this is a problem of multi-agent metadeliberation. We provide a reduction of computing the optimal deliberation-allocation policy to computing Gittins indices in multi-anned bandit worlds, and apply a modification of the dynamic-VCG mechanism to yield truthful participation in an ex post equilibrium. Our mechanism achieves equilibrium implementation ofthe optimal policy even when agents have the capacity to deliberate about other agents' valuations, and thus addresses the problem of strategic deliberation.
Citable link to this pagehttp://nrs.harvard.edu/urn-3:HUL.InstRepos:4000333
- FAS Scholarly Articles