Efficiency and equilibrium in task allocation economies with hierarchical dependencies

Authors:
William E. Walsh;Michael P. Wellman
Affiliations:
Artificial Intelligence Laboratory, University of Michigan, Ann Arbor, MI;Artificial Intelligence Laboratory, University of Michigan, Ann Arbor, MI
Venue:
IJCAI'99 Proceedings of the 16th international joint conference on Artifical intelligence - Volume 1
Year:
1999

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Abstract

We analyze economic efficiency and equilibrium properties in decentralized task allocation problems involving hierarchical dependencies and resource contention. We bound the inefficiency of a type of approximate equilibrium in proportion to the number of agents and the bidding parameters in a particular market protocol. This protocol converges to an approximate equilibrium with respect to all agents, except those which may acquire unneeded inputs. We introduce a decommitment phase to allow such agents to decommit from their input contracts. Experiments indicate that the augmented market protocol produces highly efficient allocations on average.