Fuzzy Reasoning Model for Multi Agent Negotiation Support System

Both purchaser and bargainer are two agents in this fuzzy reasoning model for multi agents negotiation support system separately. The agents exchange suggestions on the basis of the information available and negotiation strategies used by each party. The information available for both the purchaser and the bargainer involves the cost, product quality, batch, supplication date and the like. This information can be imprecise if constraints, preferences and priorities are defined as fuzzy constraints describing the level of satisfaction of an agent (and its user) with different potential solutions. The objective of an agent is to find a solution that maximizes the agent´s utility at the highest possible level of constraint satisfaction subject to its acceptability by other agents (Pareto-optimal). The transaction process was represented as two fuzzy automata. Some fuzzy rules are used in these automata to determine the next state transfer. Partiality of agent can be defined manually or automatically. Optimized negotiation results are up to personal advantage-maximal or Pareto-optimal because of adaptability of agent, robustness of fuzzy reasoning and user-defined agent partiality