Simulated Negotiation Outcomes Through Recommendation Crowding

The goal of the paper is to propose a method for finding outcomes of negotiations of multiple parties with a multi-criteria decision outcomes evaluation. Firstly, the procedure for reduction of continuous set of options to large but finite crowd of compromise recommendations is presented. Next, the crowd is integrated to a single benchmark which is treated as a proposal of artificial auxiliary player called a lone wolf as presented by Kersten and Szapiro (Proceedings of the international conference of the society of systems and science. Budapest, 1987). The strategy of negotiation with this artificial player is proposed to generate a benchmark evaluations scheme for real negotiation. Finally, a multi-agent simulation approach for multi-lateral negotiation process modeling is presented in order to estimate possible negotiation outcomes.