Multi-Agent Negotiation System Using Adaptive Fuzzy Logic in Resource Allocation

This paper addresses the multi-agent system (MAS) with negotiation capability using an artificial intelligent (AI) approach - adaptive fuzzy logic (AFL) - in learning the behavior of other agents when allocating resources. The learning continues during each reasoning process on the subsequent reaction of negotiants. We present the results of multi-agent negotiation with multi-issue (e.g. price, time, resource conditions) in three perspectives (accuracy, adaptability and reliability) with different AI and heuristic approaches. From our analysis, we found that the AFL gives an overall stable performance and outperform other methods in analyzing opponent tactics and strategies