Increasing threshold search for best-valued agents

David Same, Simon Shamoun, Eli Rata

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

This paper investigates search techniques for multi-agent settings in which the most suitable agent, according to given criteria, needs to be found. In particular, it considers the case where the searching agent incurs a cost for learning the value of an agent and the goal is to minimize the expected overall cost of search by iteratively increasing the extent of search. This kind of search is applicable to various domains, including auctions, first responders, and sensor networks. Using an innovative transformation of the extents-based sequence to a probability-based one, the optimal sequence is proved to consist of either a single search iteration or an infinite sequence of increasing search extents. This leads to a simplified characterization of the the optimal search sequence from which it can be derived. This method is also highly useful for legacy economic-search applications, where all agents are considered suitable candidates and the goal is to optimize the search process as a whole. The effectiveness of the method for both best-valued search and economic search is demonstrated numerically using a synthetic environment.

Original languageEnglish
Title of host publicationAAAI-10 / IAAI-10 - Proceedings of the 24th AAAI Conference on Artificial Intelligence and the 22nd Innovative Applications of Artificial Intelligence Conference
PublisherAI Access Foundation
Pages848-853
Number of pages6
ISBN (Print)9781577354659
StatePublished - 2010
Event24th AAAI Conference on Artificial Intelligence and the 22nd Innovative Applications of Artificial Intelligence Conference, AAAI-10 / IAAI-10 - Atlanta, GA, United States
Duration: 11 Jul 201015 Jul 2010

Publication series

NameProceedings of the National Conference on Artificial Intelligence
Volume2

Conference

Conference24th AAAI Conference on Artificial Intelligence and the 22nd Innovative Applications of Artificial Intelligence Conference, AAAI-10 / IAAI-10
Country/TerritoryUnited States
CityAtlanta, GA
Period11/07/1015/07/10

Bibliographical note

Funding Information:
We are grateful to Dick Bond, Robert Brandenberger, Brendan Crill, Robert Crittenden, Khurram Farooqui, Josh Gundersen, Wayne Hu, Kip Hyatt, Lloyd Knox, Arthur Kosowsky, Andrew Lange, Phil Lubin, Melvin Phua, Alex Polnarev, Dan Swetz, David Wilkinson, Grant Wilson, Ed Wollack, and Matias Zal-darriaga for many useful conversations. B. G. K. and C. W. O. were supported by NASA GSRP Fellowships. POLAR’s HEMT amplifiers were graciously provided by John Carlstrom. This work has been supported by NSF grants AST 93-18727, AST 98-02851, and AST 00-71213 and NASA grant NAG5-9194.

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