{"title":"Reactive Planning with Uncertainty of a Plan","authors":"Seiji Yamada","doi":"10.1109/AIHAS.1992.636887","DOIUrl":null,"url":null,"abstract":"An autonomous agent in the real world needs to do planning depending on the dynamic world. For making a planning system adaptive to the dynamic world, various methods on reactive planning have been proposed. Interleaving planning with execution is a general and natural approach. However, it has a significant problem: when planning should be switched to execution, and few solutions has been proposed. In this paper, we propose a theoretical framework in which the switching timing is determined with the success probability. The success probability represents uncertainty in the execution of a plan, and depends on a change of the real world. Furthermore, since the success probability is obtained based on causality between literals, it is smciently precise. In our method, planning is switched to executionlobservation only when the success probability decreases less than thresholds. Since the success probability is used as an evaluation function,for searching a plan, we present a new interleave planning algorithm with the success probability, and different experimental results from conventional planning are obtained.","PeriodicalId":442147,"journal":{"name":"Proceedings of the Third Annual Conference of AI, Simulation, and Planning in High Autonomy Systems 'Integrating Perception, Planning and Action'.","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1992-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Third Annual Conference of AI, Simulation, and Planning in High Autonomy Systems 'Integrating Perception, Planning and Action'.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AIHAS.1992.636887","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

Abstract

An autonomous agent in the real world needs to do planning depending on the dynamic world. For making a planning system adaptive to the dynamic world, various methods on reactive planning have been proposed. Interleaving planning with execution is a general and natural approach. However, it has a significant problem: when planning should be switched to execution, and few solutions has been proposed. In this paper, we propose a theoretical framework in which the switching timing is determined with the success probability. The success probability represents uncertainty in the execution of a plan, and depends on a change of the real world. Furthermore, since the success probability is obtained based on causality between literals, it is smciently precise. In our method, planning is switched to executionlobservation only when the success probability decreases less than thresholds. Since the success probability is used as an evaluation function,for searching a plan, we present a new interleave planning algorithm with the success probability, and different experimental results from conventional planning are obtained.
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具有计划不确定性的反应性计划
现实世界中的自主智能体需要根据动态世界进行规划。为了使规划系统适应动态环境,人们提出了各种反应性规划方法。将计划与执行交织在一起是一种普遍而自然的方法。然而,它有一个重要的问题:什么时候应该将计划转换为执行,并且提出的解决方案很少。在本文中,我们提出了一个由成功概率决定切换时间的理论框架。成功概率表示计划执行的不确定性,取决于现实世界的变化。此外,由于成功概率是基于字面之间的因果关系获得的,因此它非常精确。在我们的方法中,只有当成功概率下降小于阈值时,计划才切换到执行观察。由于以成功概率作为评价函数,在搜索方案时,提出了一种新的基于成功概率的交错规划算法,得到了不同于传统规划的实验结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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