摘要： 研究群体非玩家控制角色(NPC)如何根据具体游戏环境和剧情因素进行相互联系的协同运动以实现群体行为。在此基础上，提出一种适合网络游戏的多NPC协同运动策略，采用人工势场法描述游戏状态，并利用粒子群算法确定下一时刻每个NPC的最佳运动位置，从而实现个体NPC根据游戏状态自主完成群体作战目标。实验结果表明，该方法能够在网络游戏中保证群体NPC高效、自主地适应环境，并能较好地完成与玩家对抗的游戏任务。

关键词: 协同运动, 粒子群优化, 人工势场, 网络游戏

Abstract: For the Non-Player Character(NPC) cooperative motion which realizes the swarm behaves model in conformity to the states and scenarios of games, this paper presents a cooperative motion strategy of multi-NPC for online games, which describes games states by artificial potential field and computes the next best position of NPC by PSO. It realizes the self-determination motion of individual NPC based on the goal of collective campaign. Experimental results show that the presented method can assure that NPC confronts with the players effectively and independently in online games.

Key words: cooperative motion, PSO, artificial potential field, online games

中图分类号: 

• TP181