CAPIR: Collaborative Action Planning with Intention Recognition
CAPIR: Collaborative Action Planning with Intention Recognition
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CAPIR：具有意图识别的协作行动规划
DOI：
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发表时间：
2011
期刊：
影响因子：
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通讯作者：
A. Grant
中科院分区：
文献类型：
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作者：
T. Nguyen;David Hsu;Wee Sun Lee;T. Leong;L. Kaelbling;Tomas Lozano;A. Grant
我们应用决策理论技术来构建非玩家角色，这些角色能够在协作游戏中帮助人类玩家。该方法是基于解决马尔可夫决策过程，这可能是困难的，当游戏状态是由许多变量描述。为了扩展到更复杂的游戏，该方法允许将游戏任务分解为子任务，每个子任务都可以由马尔可夫决策过程建模。意图识别用于推断人类当前正在执行的子任务，允许助手帮助人类执行正确的任务。实验表明，该方法可以是有效的，在帮助一个人在一个合作的游戏中，给出接近人类水平的性能。
We apply decision theoretic techniques to construct non-player characters that are able to assist a human player in collaborative games. The method is based on solving Markov decision processes, which can be difficult when the game state is described by many variables. To scale to more complex games, the method allows decomposition of a game task into subtasks, each of which can be modelled by a Markov decision process. Intention recognition is used to infer the subtask that the human is currently performing, allowing the helper to assist the human in performing the correct task. Experiments show that the method can be effective, giving near-human level performance in helping a human in a collaborative game.