The PANDA Framework for Hierarchical Planning

Author:

Höller DanielORCID,Behnke Gregor,Bercher Pascal,Biundo Susanne

Abstract

AbstractDuring the last years, much progress has been made in hierarchical planning towards domain-independent systems that come with sophisticated techniques to solve planning problems instead of relying on advice in the input model. Several of these novel methods have been integrated into the PANDA framework, which is a software system to reason about hierarchical planning tasks. Besides solvers for planning problems based on plan space search, progression search, and translation to propositional logic, it also includes techniques for related problems like plan repair, plan and goal recognition, or plan verification. These various techniques share a common infrastructure, like e.g. a standard input language or components for grounding and reachability analysis. This article gives an overview over the PANDA framework, introduces the basic techniques from a high level perspective, and surveys the literature describing the diverse components in detail.

Funder

Deutsche Forschungsgemeinschaft

Projekt DEAL

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence

Reference44 articles.

1. Alford R, Behnke G, Höller D, Bercher P, Biundo S, Aha D (2016) Bound to plan: Exploiting classical heuristics via automatic translations of tail-recursive HTN problems. In: Proceedings of the 26th international conference on automated planning and scheduling (ICAPS), pp 20–28. AAAI Press

2. Alford R, Kuter U, Nau DS (2009) Translating HTNs to PDDL: A small amount of domain knowledge can go a long way. In: Proceedings of the 21st international joint conference on artificial intelligence (IJCAI), pp 1629–1634

3. Barták R, Maillard A, Cardoso RC (2018) Validation of hierarchical plans via parsing of attribute grammars. In: Proceedings of the 28th international conference on automated planning and scheduling (ICAPS). AAAI Press, pp 11–19

4. Behnke G, Bercher P, Kraus M, Schiller M, Mickeleit K, Häge T, Dorna M, Dambier M, Minker W, Glimm B, Biundo S (2020) New developments for Robert – Assisting novice users even better in DIY projects. In: Proceedings of the 30th international conference on automated planning and scheduling (ICAPS). AAAI Press

5. Behnke G, Biundo S (2018) X and more parallelism. Integrating LTL-next into SAT-based planning with trajectory constraints while allowing for even more parallelism. Intel Artif Rev Iberoam de Intel Artif 21(62):75–90

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Detecting AI Planning Modelling Mistakes – Potential Errors and Benchmark Domains;PRICAI 2023: Trends in Artificial Intelligence;2023-11-10

2. PlanX: A Toolbox for Building and Integrating AI Planning Systems;2023 IEEE International Conference on Service-Oriented System Engineering (SOSE);2023-07

3. Towards Engineering AI Planning Functionalities as Services;Service-Oriented Computing – ICSOC 2022 Workshops;2023

4. Hierarchical planning and reasoning about partially ordered plans—From theory to practice;AI Magazine;2022-12

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3