A learning-based multistage negotiation model

This work presents a learning-based multistage model for multi-issue negotiation with deadline in an incomplete information setting based on intentional agents. The model describes negotiation over the price of multi-issue. It decomposes multi-issue negotiation into multistage negotiation, and each stage has the same size. The order and number of stages are decided exogenously, and the order of issues in each stage is decided endogenously. The optimal negotiation agenda for a given decomposition of the bargaining problem based on the same size of stages is presented. In particular, the model also supports the learning capability of participating agents by building a learning system (LS) for them.