MFSCD* Lite: A situation-based path planning algorithm for agent in wargame

Path planning plays a vitally important role for agents in adversarial strategy games, and even directly determines the final success or failure at times. However, most previous studies of path planning focus on minimizing path length or cost, ignoring the growing complexity resulting from dynamic changing situations. In this paper, we propose a multi-factor situational coupling D* lite (MFSCD* lite) to address the issues above. First, this paper models important dynamic situational factors and integrates them into MFSCD* lite, allowing the planning path to dynamically fit with the changing of situation. Secondly, the buffer and extended buffer of factor-values are established to reduce the repeated calculation of situational factors in MFSCD* lite. And the update strategy is optimized to improve the efficiency of path planning. To validate the effectiveness of our method, we conduct comprehensive experiments on wargame, a typical real-time agent adversarial game. The experimental results show that MFSCD* lite can meet the needs of high-quality and fast path planning, which is better than ordinary path planning algorithms. Further, it has achieved excellent performance in major wargame competitions.