Probabilistic award strategy for contract net protocol in massively multi-agent systems

Toshiharu Sugawara*, Toshio Hirotsu, Kensuke Fukuda

*Corresponding author for this work

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

Abstract

We propose a probabilistic award selection strategy for a contract net protocol (CNP) in massively multi-agent systems (MMASs) for effective task allocations. Recent Internet and sensor network applications require sophisticated multi-agent system technologies to enable the large amounts of software and computing resources to be effectively used. Improving the overall performance of MMASs in which thousands of agents work concurrently requires a new negotiation strategy for appropriately allocating tasks to agents. Our proposed method probabilistically selects the awardee in CNP based on the statistical difference between bid values for subtasks that have different costs. We explain how our proposed method can significantly improve the overall performance of MMASs.

Original languageEnglish
Title of host publicationICAART 2010 - 2nd International Conference on Agents and Artificial Intelligence, Proceedings
Pages165-171
Number of pages7
Publication statusPublished - 2010 Sept 13
Event2nd International Conference on Agents and Artificial Intelligence, ICAART 2010 - Valencia, Spain
Duration: 2010 Jan 222010 Jan 24

Publication series

NameICAART 2010 - 2nd International Conference on Agents and Artificial Intelligence, Proceedings
Volume2

Conference

Conference2nd International Conference on Agents and Artificial Intelligence, ICAART 2010
Country/TerritorySpain
CityValencia
Period10/1/2210/1/24

Keywords

  • Contract net protocol
  • Load-balancing
  • Massively multiagent systems
  • Task and resource allocation

ASJC Scopus subject areas

  • Artificial Intelligence
  • Control and Systems Engineering

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