An improved constraint model for team tactical position selection in games

2017 
With the rapid development of agent modeling technology, the modeling of agent behavior plays an important role in simulation system especially for games and training system. As the basic part of agent behavior modeling, the modeling of Tactical Position Selection (TPS) directly affects the intelligence of agent, the reality of agent's behavior model, and the user experience. Traditional TPS formulation methods do not take team cooperation into consideration. The modeling of this factor is an important area for TPS research. This paper abstracts Team-TPS (TTPS) problem as the Constraint Satisfaction Problem (CSP) and proposes an improved synchronous backtracking algorithm based on entropy ordering to solve the issue. In order to verify the effectiveness of the proposed model, a simulation experiment was carried out. The results demonstrate that for the same tactical task, the proposed Team-TPS model can find better solutions and of high efficiency.
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