Integrating parallel interactions into cooperative search

Efrat Manisterski, David Sarne, Sarit Kraus

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


In this paper we incorporate autonomous agents' capability to perform parallel interactions into the cooperative search model, resulting in a new method which outperforms the currently used ones. As a framework for our analysis we use the electronic marketplace, where buyer agents have the incentive to search cooperatively. The new search technique is quite intuitive, however its analysis and the process of extracting the optimal search strategy are associated with several significant complexities. These difficulties are derived mainly from the unbounded search space and simultaneous dual affects of decisions taken in different world states. We provide a comprehensive analysis of the model, highlighting, demonstrating and proving important characteristics of the optimal search strategy. Consequently, we manage to come up with an efficient modular algorithm for extracting the optimal cooperative search strategy for any given environment. A computational based comparative illustration of the system performance using the new search technique versus the traditional methods is given, emphasizing the main differences in the optimal strategy's structure and the advantage of using the proposed model.

Original languageEnglish
Title of host publicationProceedings of the Fifth International Joint Conference on Autonomous Agents and Multiagent Systems
Number of pages8
StatePublished - 2006
EventFifth International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS - Hakodate, Japan
Duration: 8 May 200612 May 2006

Publication series

NameProceedings of the International Conference on Autonomous Agents


ConferenceFifth International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS


  • Cooperative search
  • Parallel
  • Search cost


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