论文标题
使用场景缝制从机械师那里产生的马里奥级别
Mario Level Generation From Mechanics Using Scene Stitching
论文作者
论文摘要
本文通过将预先生成的“场景”拼接在一起，使用代理播放的机械序列作为输入规格，为超级马里奥提供了一种水平生成方法。给定一系列机械师，我们的系统使用FI-2POP算法和一系列场景来执行自动化级别的创作。该系统输出的水平具有与目标机制序列相似但具有不同播放体验的机械序列。我们将系统与贪婪方法进行比较，该方法选择了最大化目标力学的场景。与贪婪的方法相比，我们的系统能够最大程度地提高匹配力学的数量，同时使用缝线过程减少新兴力学。
This paper presents a level generation method for Super Mario by stitching together pre-generated "scenes" that contain specific mechanics, using mechanic-sequences from agent playthroughs as input specifications. Given a sequence of mechanics, our system uses an FI-2Pop algorithm and a corpus of scenes to perform automated level authoring. The system outputs levels that have a similar mechanical sequence to the target mechanic sequence but with a different playthrough experience. We compare our system to a greedy method that selects scenes that maximize the target mechanics. Our system is able to maximize the number of matched mechanics while reducing emergent mechanics using the stitching process compared to the greedy approach.
