Analyzing Action Games: A Hybrid Systems Approach
Analyzing Action Games: A Hybrid Systems Approach
复制标题
分析动作游戏：混合系统方法
DOI：
10.1145/3337722.3337757
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发表时间：
2019
期刊：
影响因子：
--
通讯作者：
Sanfelice, RG
中科院分区：
文献类型：
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作者：
Zeleke, Y;Osborn, J;Sanfelice, RG
设计支持工具受益于关于游戏突发行为的丰富信息。为特定游戏创造成功的AI玩家能够帮助我们创造出一些这样的信息，但这是一种劳动密集型且有限的工作，因为它通常只能揭示出解决方案的存在，而不是说不存在解决方案或存在特定类型的解决方案。我们展示了一种提出和回答动作游戏中可行路径、最优路径和可达空间查询的通用方法，并设计了一种游戏关卡难度测量方法。我们将动作电子游戏角色编码为混合动力系统，并以《Flappy Bird》和《超级马里奥》为案例进行研究。
Design support tools benefit from rich information about games' emergent behavior. Inventing successful AI players for particular games can help producing some of this information, but this is both labor intensive and limited in that it can generally only reveal that a solution exists and not say that no solution exists or that certain classes of solution exist. We show a generic method for posing and answering feasible-path, optimal-path, and reachable-space queries in action games, and we devise a measure of game level difficulty. We accomplish all this by encoding action videogame characters as hybrid dynamical systems, using Flappy Bird and Super Mario as case studies.