Research On Behavior Modeling Methods In Complex Simulation System

Complex simulation system is a simulation system which consists of a certain scale ofadaptive agents whose behaivior decisions are based on local information and havenonlinear charactors. Combat simulation system is a typical example of complex simulationsystem. By modeling the behaviors of human and real weapons, computer generated forces(CGF) simulation entities could interact with the events and status in the distributedbattlefield environment. Behavior modeling includes modeling the physical model andintelligent behavior model. Intelligent behavior models are the representation of intelligentbehaviors when the commander think and make decisions in the battlefield which include:single entity’s decision-making, formation control and changing, target allocation, jointoperation model and so on. To build intelligent and realistic behavior models for complexsimulation system is the core content of the research on CGF.With the analysis on the past research results in CGF behavior modeling, it is foundthat the behavior models have been weighted too heavily towards the experiment effectsand intelligent performance and lack enough attention to the model’s reality. The Computergenerated forces requires not only the similar behaviors with real forces, but also need tobuild the similar internal procedure which is helpful to improve the reality and achieve theultimate goal of computer aided campaign drilling. Besides, with the expansion ofsimulation scale, behavior modeling of aggregated CGF has also been a hot topic in CGFfield.The main content of this paper are:(1) A motivation based entity behavior models output framework is presented. Basedon the analysis on the pattern that behavior is decided by task, environment and internalstatus in combat simulation, it is thought that there are some problems about combinationexplosion and lacking flexibility. By designing a number of basic behavior models andsetting motivation set for CGF entities, a new behavior models output framework in whichtask, environment and internal status decides motivations, then the motivations decidebehaviors is established. Meanwhile the motivations’ updating mode and action selectinglogic are designed.(2) A method of CGF formation control with enhanced reality is proposed. In order toimprove the unreasonable behaviors of entities in traditional formation control, a trajectory based following behavior is used to improve follower entities’ performance in verticaldirection and the follower entities’ over-depending on leader entity is adjusted. Furthermore,the aim path-planning in formation change is achieved through generic algorithm. Byreducing the entities’ sequences difference between initial formation and final formation,the formation changing process becomes more reasonable and realistic, and the possibilityof collision was significantly reduced.(3) A consistency enhanced multi-resolution modeling method of task is presented. Byresearching on the multi-resolution modeling methods, the features and origins ofinconsistency problem are analyzed, and some consistency enhanced attributes mappingmethods are designed for the entities attributes in different levels of resolution. Besides, theentities’ task information is thought more important than other attributes and should havemore requirements of consistency. Consequently, the task information of entities isextracted and is built multi-resolution entity (MRE) model. Then, the process strategy ofconcurrent interactions is proposed for the model. Finally, the superiority ofcost-effectiveness is proved by analyzing and calculating.(4) The implementation methods of CGF behavior models in practical combatsimulation systems are designed. The CGF behavior models presented in this paper areapplied in a ground military simulation system, then the construction process of CGFcombat simulation and detailed implementation methods of the behavior models aredesigned.