Abstract:

In uncertain battlefield situations, tactical intention recognition is a critical element for understanding the tactical situation and predicting the coming course of action of the enemies. How to integrate intention recognition into a behavior model of simulated combat entities is a challenging problem and how to represent the uncertain elements relating to enemy’s intention and their uncertain relations is essential issues in intention inference. Through analyzing the factors that impact tactical intentions of the enemy and the methods that denote uncertain relations among these factors, the multi-entity Bayesian network (MEBN) is presented to denote tactical intention of the enemy. MEBN expresses the influence factors by first order logic and enhances the ability of describing the uncertain problem. MEBN adopts entity fragments for describing the military domain knowledge and so it is easy reused. A knowledge-based constructing model algorithm is proposed for dynamic constructing a tactical intention model based on the knowledge base of enemy intention. Finally, a simple example of tactical intention recognition is given. The results show that the method is available and efficient.