Journal
APPLIED ARTIFICIAL INTELLIGENCE
Volume 21, Issue 6, Pages 489-527Publisher
TAYLOR & FRANCIS INC
DOI: 10.1080/08839510701408971
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Automated negotiation is a powerful (and sometimes essential) means for allocating resources among self-interested autonomous software agents. A key problem in building negotiating agents is the design of the negotiation strategy, which is used by an agent to decide its negotiation behavior. In complex domains, there is no single, obvious optimal strategy. This has led to much work on designing heuristic strategies, where agent designers usually rely on intuition and experience. In this article, we introduce STRATUM, a methodology for designing strategies for negotiating agents. The methodology provides a disciplined approach to analyzing the negotiation environment and designing strategies in light of agent capabilities and acts as a bridge between theoretical studies of automated negotiation and the software engineering of negotiation applications. We illustrate the application of the methodology by characterizing some strategies for the Trading Agent Competition and for argumentation-based negotiation.
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