通过MAP-精英照亮敌人的空间
Illuminating the Space of Enemies Through MAP-Elites
摘要：
冒险游戏有几个挑战要克服，其中最常见的是敌人。敌人的目标是通过夺取生命值来阻碍玩家的进步，而他们阻碍这种进步的方式对于不同类型的敌人来说是不同的。在这种情况下，本文介绍了一个扩展版本的进化方法，程序生成的敌人，目标敌人的困难为目标。我们的方法通过结合MAP-精英群体来生成不同的敌人而不损失质量，从而推进了敌人生成研究。计算实验表明，该方法收敛大多数敌人在MAP精英在不到一秒的大多数情况下。除此之外，我们还对玩过一个带有我们生成的敌人的冒险游戏原型的玩家进行了实验。这个实验表明，玩家喜欢他们玩的大多数关卡，我们成功地创造了被认为容易、中等或难以面对的敌人。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
