Delete- and Ordering-Relaxation Heuristics for HTN Planning

Höller, Daniel; Bercher, Pascal; Behnke, Gregor

doi:10.24963/ijcai.2020/564

Cited by 6 publications

(8 citation statements)

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“…Directly motivated by the design of heuristics, we also investigated the complexity of delete‐relaxed HTN problems with empty ordering constraints. We showed this problem to be NP‐complete (Höller, Bercher, and Behnke 2020), which is in line with results by Alford et al. (2014) who showed it for delete‐relaxed HTN problems (i.e., without the relaxation of ignoring all ordering constraints).…”

Section: Theoretical Investigationssupporting

confidence: 89%

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Hierarchical planning and reasoning about partially ordered plans—From theory to practice

Bercher

2022

AI Magazine

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This invited paper (part of the New Faculty Highlights Invited Speaker Program of AAAI'21*) surveys my work done until today. The reviewed work focuses on hierarchical task network (HTN) planning as well as on partial order causal link (POCL) planning. Lines of research include theoretical investigations (mostly computational complexity analyses), heuristic search, as well as the practical application of the technology for planning-based assistants, which support a human user in carrying out various tasks.

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Section: Theoretical Investigationssupporting

confidence: 89%

“…Section 3.2 mentioned that we proved NP‐completeness of delete‐ and ordering‐free HTN problems (Höller, Bercher, and Behnke 2020). In the same work, we exploit this by encoding this problem into an ILP, one of the best‐known frameworks for efficiently solving NP‐complete problems.…”

Section: Heuristic Search In Htn Planningmentioning

confidence: 99%

Hierarchical planning and reasoning about partially ordered plans—From theory to practice

Bercher

2022

AI Magazine

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“…• Plan space search [15,16,18,21,22] • Progression search [31][32][33][34]36] • Compilation to propositional logic for…”

Section: The Problem Definition Language Hddlmentioning

confidence: 99%

“…We recently described two new heuristic approaches. In the family of heuristics presented in Höller et al [32], we first relax the delete effects in all actions and the ordering relations in all methods and then solve the resulting problem using integer programming.…”

Section: Heuristic Progression Searchmentioning

confidence: 99%

The PANDA Framework for Hierarchical Planning

et al. 2021

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During 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.

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“…Other techniques have been extended, e.g. propositional encodings for SATbased planners Biundo 2018, 2019;Schreiber et al 2019), or IP encodings for heuristics (Höller, Bercher, and Behnke 2020). Alford et al (2009; introduced translations from HTN problems into classical problems by adding a new part to the state of the problem representing the decomposition process.…”

Section: Introductionmentioning

confidence: 99%

Translating Totally Ordered HTN Planning Problems to Classical Planning Problems Using Regular Approximation of Context-Free Languages

Höller

2021

ICAPS

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There have been several approaches to use techniques from classical planning in HTN planning. While a direct translation is in general not possible due to the different expressiveness, there have been translations of bounded HTN problems and approaches to use classical heuristics in HTN search procedures. In this paper, we introduce a different approach. We exploit methods from the field of Computational Linguistics introduced to approximate Context-Free Languages by Finite Automata. We use them to approximate the decomposition structure of Totally Ordered (TO) HTN planning problems by classical problems. The resulting problem can then be solved using standard classical planning systems. A subset of TOHTN problems can be translated exactly, i.e., without changing the set of solutions. For problems where an approximation is necessary, we use an overapproximation, i.e., the set of solutions to the classical problem is a superset of that of the HTN problem. We then use plan verification to check whether a solution is valid and thus obtain a sound and complete overall approach. The resulting system outperforms the state of the art on the IPC 2020 benchmark set in terms of coverage.

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Delete- and Ordering-Relaxation Heuristics for HTN Planning

Cited by 6 publications

References 1 publication

Hierarchical planning and reasoning about partially ordered plans—From theory to practice

Hierarchical planning and reasoning about partially ordered plans—From theory to practice

The PANDA Framework for Hierarchical Planning

Translating Totally Ordered HTN Planning Problems to Classical Planning Problems Using Regular Approximation of Context-Free Languages

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