A Negotiation Model for Large Scale Multi-Agent Systems

Modeling agent negotiation is of key importance in building multi-agent systems, because negotiation is one of the most important types of agent interaction. Negotiation provides the basis for managing the expectations of the individual negotiating agents, and it enables selecting solutions that satisfy all the agents as much as possible. Thus far, most negotiation models have serious limitations and weaknesses when employed in large-scale multi-agent systems. Yet, large-scale multi-agent systems find their use in major domains of human development, such as space exploration, military technology, disaster response systems, and health technology. This paper presents a negotiation model for large-scale multi-agents systems that is based on Qualitative Reasoning and Game Theory, and on the similarity criteria. In the model, each agent classifies its negotiation opponents according to the similarity of their preference model. The agents use Qualitative Reasoning components of the negotiation model to estimate the preference models of their negotiation opponents, and to determine the “amount” of tradeoff associated with the various solution options. Moreover, they use the Game Theory component of the negotiation model to determine the social-acceptance of each of the solution options. The output of the Qualitative Reasoning and Game Theory components of the negotiation model is used to determine the rationale for accepting or rejecting offers made by the negotiation opponents of the agents.