概率性计划可读性：使用现成规划器
Probabilistic Plan Legibility with Off-the-shelf Planners
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中文总结 AI 辅助
本文提出一种利用现成规划器在任意PDDL领域实现概率性计划可读性的方法，通过二阶心智理论估计观察者视角，并证明可读性与效率需权衡，需正则化因子平衡。
中文摘要 AI 辅助
可读性规划是指从观察者的角度，创建能够最好地从一组其他候选计划中消除其目标歧义的计划。在本文中，我们提出了一种针对任意PDDL领域的可读性规划方法，通过将先前关于可读性的研究扩展到经典规划，而无需构建专门的规划器。我们还讨论了如何通过二阶心智理论来估计观察者的视角，该理论连接了规划者和观察者的任务空间。我们的解决方案例如可以部署在人机协作场景中，其中团队中的自主机器人可以通过生成可读性计划来隐式地传达其目标。我们在多个PDDL规划领域上展示了基准测试结果。我们的结果普遍表明，计划可读性与计划效率之间存在权衡，然而，并非所有规划领域都能以相同方式提高可读性，并且证明需要一个正则化因子来平衡可读性和效率。
英文摘要
Legible planning is the creation of plans that best disambiguate their goals from a set of other candidates from an observer's perspective. In this paper we propose a method for legible planning for arbitrary PDDL domains, by extending previous research on legibility to classical planning without requiring to construct ad-hoc planners. We also discuss how the observer perspective may be estimated through a second order theory of mind that connects the planner's and the observer's task spaces. Our solution can for example be deployed in human-robot teaming scenarios, where an autonomous robot in a team can implicitly communicate its goal by producing legible plans. We present benchmark results on several PDDL planning domains. Our results generally show that plan legibility is a trade-off with plan efficiency, however, not all planning domains allows to increase legibility in the same way and a regularizing factor to balance legibility and efficiency was proved necessary.
发表机构
- Umeå University（于默奥大学）
机构由 AI 辅助整理，请以论文原文为准。
