论文标题
通过地图精英照亮敌人的空间
Illuminating the Space of Enemies Through MAP-Elites
论文作者
论文摘要
动作冒险游戏有几个挑战需要克服，最常见的是敌人。敌人的目标是通过占据生命点来阻碍玩家的进步，而他们阻碍了这种进步在不同种类的敌人方面与众不同。在这种情况下，本文介绍了一种扩展版本的进化方法，用于生成针对敌人难以作为目标的敌人。我们的方法通过纳入地图精英人群来产生不同的敌人而不会失去质量来推动敌人的生成研究。计算实验表明，在大多数情况下，在不到一秒钟的时间内，MAP-ELITE中的大多数敌人都会收敛。此外，我们尝试了与我们产生的敌人一起玩动作冒险游戏原型的玩家。该实验表明，玩家享受了他们所玩的大多数水平，我们成功地创造了被认为是简单，中等或难以面对的敌人。
Action-Adventure games have several challenges to overcome, where the most common are enemies. The enemies' goal is to hinder the players' progression by taking life points, and the way they hinder this progress is distinct for different kinds of enemies. In this context, this paper introduces an extended version of an evolutionary approach for procedurally generating enemies that target the enemy's difficulty as the goal. Our approach advances the enemy generation research by incorporating a MAP-Elites population to generate diverse enemies without losing quality. The computational experiment showed the method converged most enemies in the MAP-Elites in less than a second for most cases. Besides, we experimented with players who played an Action-Adventure game prototype with enemies we generated. This experiment showed that the players enjoyed most levels they played, and we successfully created enemies perceived as easy, medium, or hard to face.
