基于粒子群优化的FPS电子游戏非玩家角色进化行为设计

Guillermo Díaz, A. Iglesias
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引用次数: 2

摘要

进化计算涵盖了受自然和生物进化启发的人工智能技术家族。这些方法,如群体智能,可能会对电子游戏产生非常积极的影响,例如,对于非玩家角色(npc)的设计,以一种简单的方式获得现实的智能行为。为此,我们描述了一款第一人称射击电子游戏中使用粒子群优化的npc进化行为设计。通过计算机实验分析了该方法的可行性和性能。实验结果表明,所提出的方法具有良好的性能,可以成功地在全自动(即没有任何人工参与者)和高效的方式下使用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Evolutionary Behavioral Design of Non-Player Characters in a FPS Video Game Through Particle Swarm Optimization
Evolutionary computation covers the family of artificial intelligence techniques inspired by nature and biological evolution. These methods, such as swarm intelligence, may have a very positive impact on video games, for instance, for the design of Non-Player Characters (NPCs) to obtain a realistic intelligent behavior in a simple way. To this aim, we describe an evolutionary behavioral design of NPCs using particle swarm optimization in a first-person shooter video game. Several computer experiments have been carried out to analyze the feasibility and performance of this approach. Our experimental results show that the proposed method performs very well and can be successfully used in a fully automatic (i.e., without any human player) and efficient way.
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