Feasibility Study: Moving Non-Homogeneous Teams in Congested Video Game Environments
Feasibility Study: Moving Non-Homogeneous Teams in Congested Video Game Environments
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DOI：
10.1609/aiide.v13i1.12919
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发表时间：
2017-10
期刊：
影响因子：
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通讯作者：
Hang Ma;Jingxing Yang;L. Cohen;T. K. S. Kumar;Sven Koenig
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文献类型：
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作者：
Hang Ma;Jingxing Yang;L. Cohen;T. K. S. Kumar;Sven Koenig
多代理路径查找（MAPF）是人工智能中一个充分研究的问题，在该问题中，人们需要找到具有给定启动和目标位置的代理的无冲突路径。在视频游戏中，不同类型的代理通常会形成团队。在本文中，我们演示了人工智能中MAPFALGORITHM在拥挤的视频游戏环境中移动此类非均匀团队的有用性。
Multi-agent path finding (MAPF) is a well-studied problem in artificial intelligence, where one needs to find collision-free paths for agents with given start and goal locations. In video games, agents of different types often form teams. In this paper, we demonstrate the usefulness of MAPFalgorithms from artificial intelligence for moving such non-homogeneous teams in congested video game environments.