A Study on Game Theory in Decision Interaction for Multi Intelligent Agents Based on Information Fusion

variation tendency of situation of an interaction system combined by multi intelligent agent is pushed forward by their respective decision process, pure probability and evidence theory are not satisfying available tools for this type of prediction. For these predictions, game theory can provide preferable decision and recognition, and is a tool of Process Planning. By combining influence diagrams with game theory, we proposed a new architecture Bayesian Game Model for decision support to enhance capability of the awareness and prediction for a complex situation caused by multi interactive intelligent agents. In this paper, we discuss Bayesian game architecture and the related algorithm for a situation evolution under the circumstance of multi-source information fusion containing multi intelligent agents. Compared with other high level information fusion models containing decision makers and environmental status, this method can provide better decision effect. By combining with game theory, the proposed method provide a Joint probability distribution for whole situation in the form of Bayesian game and make the decision maker's game strategies to be reflected in situation evolution.