OAR: A formal framework for multi-agent negotiation

Jiaying Shen, Ingo Weber, Victor Lesser

Research output: Contribution to conferencePaperpeer-review

2 Scopus citations

Abstract

In Multi-Agent systems, agents often need to make decisions about how to interact with each other when negotiating over task allocation. In this paper, we present OAR, a formal framework to address the question of how the agents should interact in an evolving environment in order to achieve their different goals. The traditional categorization of self-interested and cooperative agents is unified by adopting a utility view. We illustrate mathematically that the degree of cooperativeness of an agent and the degree of its self-directness are not directly related. We also show how OAR can be used to evaluate different negotiation strategies and to develop distributed mechanisms that optimize the performance dynamically. This research demonstrates that sophisticated probabilistic modeling can be used to understand the behaviors of a system with complex agent interactions.

Original languageEnglish
Pages176-183
Number of pages8
StatePublished - 2005
Externally publishedYes
Event20th National Conference on Artificial Intelligence and the 17th Innovative Applications of Artificial Intelligence Conference, AAAI-05/IAAI-05 - Pittsburgh, PA, United States
Duration: 9 Jul 200513 Jul 2005

Conference

Conference20th National Conference on Artificial Intelligence and the 17th Innovative Applications of Artificial Intelligence Conference, AAAI-05/IAAI-05
Country/TerritoryUnited States
CityPittsburgh, PA
Period9/07/0513/07/05

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