Multi behavior NPC coordination using fuzzy coordinator and Gaussian distribution

M. Akbar, Wida Praponco, M. Hariadi, Supeno Mardi S N
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引用次数: 5

Abstract

Nowadays, Artificial Intelligence (AI) techniques have an important role in modern computer games especially to make NPCs in games more human-like, believable and natural. In a real time warfare game, coordination of NPC troops can create a deeper sense of immersion. Anyhow, multi behavior NPC troops have intelligence for selecting their behavior itself which sometimes does not appropriate to accomplish a team objective. Therefore, in this research we propose to develop smart agent for team coordination to produce better team behavior. Fuzzy coordinator method is employed for team coordination based on smart agent as a leader in attacking scenario. The smart agent coordinates a team strategy with uncoordinated action from the NPC to produce coordinated action for each NPC. Gaussian distribution is used to make variation action of each NPC more natural and unpredictable. The experiment demonstrates the smart agent with fuzzy coordinator who becomes the leader can analyze attack time remaining, health of each NPC and enemy to decide which one has to offense or defense in battle by change decision of each NPC troop to select action that has contribution for team.
基于模糊协调器和高斯分布的多行为NPC协调
如今,人工智能(AI)技术在现代电脑游戏中发挥着重要作用,尤其是使游戏中的npc更像人类,更可信,更自然。在实时战争游戏中,NPC部队的协作可以创造出更深层次的沉浸感。无论如何,多行为NPC部队具有选择自己行为的智能,这有时并不适合完成团队目标。因此,在本研究中,我们提出开发团队协调的智能代理,以产生更好的团队行为。在攻击场景下,采用模糊协调器方法进行基于智能代理的团队协调。智能代理协调NPC不协调行动的团队策略,为每个NPC产生协调行动。采用高斯分布,使每个NPC的变异动作更加自然和不可预测。实验表明,具有模糊协调器的智能代理作为领导者,可以通过改变每个NPC部队的决策来选择对团队有贡献的行动,从而分析战斗中每个NPC和敌人的剩余攻击时间、生命值来决定进攻或防御。
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