Terrain Analysis in Real-Time Strategy Games: An Integrated Approach to Choke Point Detection and Region Decomposition
Terrain Analysis in Real-Time Strategy Games: An Integrated Approach to Choke Point Detection and Region Decomposition
复制标题
实时策略游戏中的地形分析：阻塞点检测和区域分解的综合方法
DOI：
--
复制
发表时间：
2010
期刊：
影响因子：
--
通讯作者：
Luke Perkins
中科院分区：
文献类型：
--
作者：
Luke Perkins
实时策略（RTS）游戏中的自治代理缺乏一个集成的框架来推理其环境中的开放空间的瓶颈点和区域。本文提出了一种算法，该算法将环境划分为一组多边形区域，并计算相邻区域之间的最佳阻塞点。这种表示可以用作AI代理的组件，以推理地形，计划多条攻击路线，并做出其他战术决策。该算法在国际星际争霸比赛中常用的一组流行地图上进行测试，并根据人类参与者的答案进行评估。该算法识别了参与者发现的97%的瓶颈点，还识别了一些人类参与者没有识别为瓶颈点的瓶颈。
Autonomous agents in real-time strategy (RTS) games lack an integrated framework for reasoning about choke points and regions of open space in their environment. This paper presents an algorithm which partitions the environment into a set of polygonal regions and computes optimal choke points between adjacent regions. This representation can be used as a component for AI agents to reason about terrain, plan multiple routes of attack, and make other tactical decisions. The algorithm is tested on a set of popular maps commonly used in international Starcraft competitions and evaluated against answers made by human participants. The algorithm identified 97% of the choke points that the participants found and also identified a number of bottlenecks that human participants did not recognize as choke points.