Harnessing the search for rational bid schedules with stochastic search and domain-specific heuristics

Alexander Babanov, John Collins, Maria L Gini

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations

Abstract

In previous work we proposed an approach for computing an agent's preferences over different schedules of tasks, and for soliciting desirable bid combinations to cover the tasks. The proposed approach finds schedules that maximize the agent's Expected Utility. The maximization problem is hard because the domain is piece-wise continuous, with the number of pieces and local maxima growing exponentially in the worst case scenario. For agents who are averse to taking risks, maximization algorithms tend to converge to degenerate maxima of no practical interest. In this paper we demonstrate three maximization methods based on domain-specific heuristics. We also present a new stochastic maximization approach, and benchmark it in two substantially different problem setups.

Original languageEnglish (US)
Title of host publicationProceedings of the Third International Joint Conference on Autonomous Agents and Multiagents Systems, AAMAS 2004
EditorsN.R. Jennings, C. Sierra, L. Sonenberg, M. Tambe
Pages269-276
Number of pages8
StatePublished - Sep 27 2004
EventProceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS 2004 - New York, NY, United States
Duration: Jul 19 2004Jul 23 2004

Publication series

NameProceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS 2004
Volume1

Other

OtherProceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS 2004
CountryUnited States
CityNew York, NY
Period7/19/047/23/04

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