Battlefield situation understanding based on fuzzy logic and CBR

To simulate battalions and regimental level battlefield combat, intelligent agent technique is often used to model troops on the battlefield. To enable agents to understand battlefield situation and perform basic tactics, there are great difficulties lie in the following aspects: the perception and understanding of battlefield information are often vague rather than precise; high-dimensional data of battlefield make domain rules hard to extract and knowledge base difficult to construct; huge amount of battlefield simulation data cause system delay. This paper presents a hybrid approach based on fuzzy logic and case-based reasoning, employs frame structure as case knowledge representation to simplify domain knowledge acquisition process. The introduction of Fuzzy Logic, in the case of properties matching process allows the Agent to deal with ambiguity and uncertainty of battlefield combat knowledge. The case study shows that the proposed hybrid approach combines both advantages of Fuzzy Logic and CBR, and its usability is plain to see.