排序规划和/或向前搜索析取表示Contingent Planning as AND/OR Forward Search with Disjunctive Representation |
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课程网址: | http://videolectures.net/icaps2011_to_contingent/ |
主讲教师: | Son Thanh To |
开课单位: | 新墨西州州立大学 |
开课时间: | 信息不详。欢迎您在右侧留言补充。 |
课程语种: | 英语 |
中文简介: | 本文介绍了一种具有高度竞争力的条件规划方法,该方法将信念状态编码为析取范式公式。2009年),在信仰状态空间寻找解决方案。在(等)。2009年),定义了一个完整的过渡函数,用于计算存在不完整信息的后继信念状态。这项工作扩展了在或有计划解决方案的和/或前向搜索范式中处理非确定性和感知行为的功能。该函数允许在合理假设下,有效地计算后续信念状态,即多项式时间。本文还提出了一种和/或搜索算法的新变种,称为prao(删减和/或搜索),它使规划人员能够显著地删减搜索空间;此外,当找到一个解时,剩余的搜索图也是条件规划问题的解树。这些技术的优势是通过从文献中提供的大量基准获得的经验结果来证实的。 |
课程简介: | This paper introduces a highly competitive contingent planner, that uses the novel idea of encoding belief states as disjunctive normal form formulae (To et al. 2009), for the search for solutions in the belief state space. In (To et al. 2009), a complete transition function for computing successor belief states in the presence of incomplete information has been defined. This work extends the function to handle non-deterministic and sensing actions in the AND/OR forward search paradigm for contingent planning solutions. The function allows one, under reasonable assumptions, to compute successor belief states efficiently, i.e., in polynomial time. The paper also presents a novel variant of an AND/OR search algorithm, called PrAO (Pruning AND/OR search), which allows the planner to significantly prune the search space; furthermore, by the time a solution is found, the remaining search graph is also the solution tree for the contingent planing problem. The strength of these techniques is confirmed by the empirical results obtained from a large set of benchmarks available in the literature. |
关 键 词: | 完整转换函数; 搜索空间; 队伍规划问题 |
课程来源: | 视频讲座网 |
最后编审: | 2019-11-18:cwx |
阅读次数: | 50 |