A Bayesian Learning Model in the Agent-based Bilateral Negotiation between the Coal Producers and Electric Power Generators

The reform of Chinapsilas coal sector has changed the traditional relationship of the coal producers and electric power generators, and now most of the coal the coal producers sell to the generators is transacted through electric coal bilateral contracts, whose price is negotiated in advance. However, long time and low efficiency always come along with the negotiation process, so in this paper, the agent-based negotiation environment was designed for the negotiators so as to reduce the negotiation time, and a Bayesian learning model is designed to enhance the negotiator agentpsilas adjust ability to the dynamic environment. The final example proved that the Bayesian learning model can help the agent obtain more accurate information about its opponent through the negotiation process and bid more efficiently, so the negotiation time is reduced and its efficiency is improved.