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A Plan Recognition Algorithm Based on the Probabilistic Goal Graph

机译:基于概率目标图的计划识别算法

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Based on the Goal Graph, we construct a new structure named Probabilistic Goal Graph(PGG), which uses the goal nodes instead of state nodes, and adds the observation nodes. According to the background knowledge, we calculate the probability distribution of the observed actions, and then calculate the probability of each goal node, ultimately get an optimal plan which has maximum probability to achieve the goal. By putting the probabilistic values into the goal graph, it can be effectively recognized the partial observed actions, and overcomes the defects that the goal recognition algorithm can not find the optimal plan.
机译:基于目标图,我们构造了一个新的结构,称为概率目标图(PGG),该结构使用目标节点而不是状态节点,并添加观察节点。根据背景知识,计算观察到的动作的概率分布,然后计算每个目标节点的概率,最终得到具有最大概率实现目标的最优计划。通过将概率值放入目标图中,可以有效地识别部分观察到的动作,克服了目标识别算法找不到最优计划的缺陷。

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