Abstract Planning deals with the task of finding an ordered set of actions that achieves some goals from an initial state. In many real-world applications it is unfeasible to find a plan achieving all goals due to limitations in the available resources. A common case consists of having a bound on a given cost measure that is less than the optimal cost needed to achieve all goals. Oversubscription planning (OSP) is the field of Automated Planning dealing with such kinds of problems. Usually, OSP generates plans that achieve only a subset of the goals set. In this paper we present a new technique to a priori select goals in no-hard-goals satisficing OSP by searching in the space of subsets of goals. A key property of the proposed approach is that it is planner-independent once the goals have been selected; it creates a new non-OSP problem that can be solved using off-the-shelf planners. Extensive experimental results show that the proposed approach outperforms state-of-the-art OSP techniques in several domains of the International Planning Competition.

中文翻译：

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使用宽松计划选择超额认购计划的目标

摘要规划处理寻找从初始状态实现某些目标的有序操作集的任务。在许多实际应用中，由于可用资源的限制，找到实现所有目标的计划是不可行的。一个常见的情况是给定成本度量的界限小于实现所有目标所需的最佳成本。超额订阅计划 (OSP) 是处理此类问题的自动计划领域。通常，OSP 生成的计划仅实现目标集的一个子集。在本文中，我们提出了一种新技术，通过在目标子集空间中搜索来满足 OSP 的非硬目标中的先验选择目标。所提议方法的一个关键特性是，一旦选定目标，它就与计划者无关；它创建了一个新的非 OSP 问题，可以使用现成的规划器来解决。广泛的实验结果表明，所提出的方法在国际规划竞赛的多个领域中优于最先进的 OSP 技术。