A Fuzzy Bayesian Learning Model in Agent-based Electric Power Bilateral Negotiation
Wang Cheng-wen · Proceedings of the CSEE · 2009
In Agent-based electric power bilateral negotiation,it is important to enhance the Agent's ability to adjust according to the environment so as to improve the negotiation efficiency.By introducing Bayesian learning to Agent-based electric power bilateral negotiation,the Agent was empowered the ability to learn according to a dynamic environment and adjust itself,so that the efficiency of the negotiation was improved.At the same time,taking into account the fuzzy uncertainties of the negotiating environment,the fuzzy set and fuzzy probability theories were used to construct an Agent Fuzzy Bayesian learning model,and then its point bidding strategy and interval bidding strategy were designed.Finally,an example was given to prove that the negotiation where both the negotiators adopt fuzzy Bayesian learning is more efficient than the negotiation where neither or only one negotiator adopt fuzzy Bayesian learning.And the interval bidding strategy can save more time for negotiators,so it is more suitable for time-limited negotiation.