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针对广义计划使用古典规划者搜索

Directed Search for Generalized Plans Using Classical Planners
课程网址: http://videolectures.net/icaps2011_srivastava_planners/  
主讲教师: Siddharth Srivastava
开课单位: 马萨诸塞大学
开课时间: 2011-07-21
课程语种: 英语
中文简介:
我们考虑在规划期间物体数量可能未知且无界的情况下找到可证明正确的广义计划的问题。输入是域规范,目标条件,以及要解决的一类具体问题实例或初始状态,以抽象的一阶表示表示。从一个空的广义计划开始,我们的总体方法是通过识别无法解决的问题实例,调用经典计划程序来解决该问题,推广所获得的解决方案并将其合并回广义计划,从而逐步提高计划的适用性。 。本文的主要贡献是(a)生成和解决现有广义计划尚未涵盖的小问题实例,(b)在具体经典计划和抽象计划表示之间进行转换,以及(c)扩展部分广义计划和增加它们的适用性。我们分析这些方法的理论属性,证明它们的正确性,并通过实验说明它们的可扩展性。由此产生的混合方法表明,仅解决一些小的经典规划问题就足以产生一个广义的计划,该计划适用于未知数量的对象的无限多个问题。
课程简介: We consider the problem of finding provably correct generalized plans for situations where the number of objects may be unknown and unbounded during planning. The input is a domain specification, a goal condition, and a class of concrete problem instances or initial states to be solved, expressed in an abstract first-order representation. Starting with an empty generalized plan, our overall approach is to incrementally increase the applicability of the plan by identifying a problem instance that it cannot solve, invoking a classical planner to solve that problem, generalizing the obtained solution and merging it back into the generalized plan. The main contributions of this paper are methods for (a) generating and solving small problem instances not yet covered by an existing generalized plan, (b) translating between concrete classical plans and abstract plan representations, and (c) extending partial generalized plans and increasing their applicability. We analyze the theoretical properties of these methods, prove their correctness, and illustrate experimentally their scalability. The resulting hybrid approach shows that solving only a few, small, classical planning problems can be sufficient to produce a generalized plan that applies to infinitely many problems with unknown numbers of objects.
关 键 词: 输入; 推广计划; 可扩展性
课程来源: 视频讲座网
最后编审: 2020-06-29:zyk
阅读次数: 53