首页> 外文会议>Proceedings of the 2007 International Conference on Machine Learning and Cybernetics >COMBINE INCREMENTAL PLANNING, REASONABLE ORDERING, EXTERNAL INFORMATION AND SOFT GOALS HANDLING
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COMBINE INCREMENTAL PLANNING, REASONABLE ORDERING, EXTERNAL INFORMATION AND SOFT GOALS HANDLING

机译:组合渐进式计划,合理的订购,外部信息和软目标处理

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Partial satisfaction or Over-subscription Planning problems arise in many real world applications, and these soft problem goals have been defined as preferences in PDDL3.0[5].Planning with over-subscription problem and preferences is one of the most challenging problems in planning.Inspired by the following two facts, we come up with a method to handle soft goals problem, and it also efficient with classical planning problems.Firstly, using external information has turned out to be a fruitful approach for classical planning; secondly, strategies in incremental planning for ordering and grouping subproblems partitioned by the subgoals of a planning problem have recently draw a lot attention from planning community.In this paper we present an approach to combining incremental planning with control knowledge and this approach can be used to handle soft goals.Our method improved incremental planning using goal agenda with more ordering for atomic goal and grouping subproblems partitioned by the subgoals.We also provide preliminary empirical results in a planner called FF04 which demonstrate the effectiveness of our approach in comparison to the original FF[6] and it can handle soft goals problem.
机译:部分满意度或超额预订计划问题出现在许多现实应用中,这些软问题目标已被定义为PDDL3.0中的首选项。[5]具有超额预订问题和首选项的计划是计划中最具挑战性的问题之一受到以下两个事实的启发,我们提出了一种处理软目标问题的方法,该方法对于经典计划问题也很有效。其次,用于计划问题的子目标划分的子问题的排序和分组的增量计划策略最近引起了计划界的广泛关注。本文提出了一种将增量计划与控制知识相结合的方法,该方法可用于处理软目标。我们的方法使用目标议程改进了增量计划,对原子目标进行了更多排序,并按子目标划分了子问题。我们还在称为FF04的计划程序中提供了初步的实证结果,证明了与原始FF相比,该方法的有效性。 [6]它可以处理软目标问题。

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