Efficient agent-based negotiation by predicting opponent preferences using AHP

Negotiation is a process essential for a wide range of applications. The complex decision making involved in negotiation makes its automation difficult. The complexity is further increased as negotiators hide their individual preferences from each other to avoid exploitation by the opponent. Even though sharing of private preference information leads to better agreement for both sides, it is never done in the absence of trust. In this work, we learn opponent’s preference information from the offers given by the opponent using Analytic Hierarchy Process (AHP). We apply our approach to the negotiation of Quality-of-Service (QoS) parameters for the establishment of Service Level Agreements (SLA) between a provider and a consumer. Experiments show that using AHP, the negotiations are faster and the agreements are on or nearer to the pareto-optimal line.