Complexity results for HTN planning

Erol, Kutluhan; Handler, James; Nau, Dana S.

doi:10.1007/bf02136175

Cited by 168 publications

(235 citation statements)

References 7 publications

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“…There is a proof [2], based on converting the planning problem to grammars and then showing, that STRIPS-like planning corresponds with regular grammars and HTN-like planning corresponds with context-free grammars. This way, it is shown that the HTN-like planning covers a wider class of possible planning domains.…”

Section: Expressivitymentioning

confidence: 99%

“…On the other hand, the theoretical HTN model is not usable in practice, as it is undecidable, even under severe restrictions. HTN remains generally undecidable even if no variables are allowed, as long as there is the possibility that a task network can contain two non-primitive tasks without specifying the order of their execution [2].…”

Section: Expressivitymentioning

confidence: 99%

“…In practice, modifications are used, restricting the plan space to finite and making the problem decidable [2].…”

Section: Expressivitymentioning

confidence: 99%

“…As a result, STRIPS-like planning expressivity is not smaller than the expressivity of HTN-like planning. The second half of the proof, showing that HTN-like planning expressivity is not smaller than the expressivity of STRIPS-like planning, is constructive, can be found in [2] and is based on the transformation of STRIPS-like domain to a flat HTN-like domain with decomposition depth 0.…”

Section: Expressivitymentioning

confidence: 99%

“…This question was answered positively in the past [2]. The proof was, however, based on the assumption, that the HTN planner can use an infinite set of symbols to mark the tasks.…”

Section: Introductionmentioning

confidence: 99%

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Expressivity of STRIPS-Like and HTN-Like Planning

Lekavý

Návrat

2007

Agent and Multi-Agent Systems: Technologies and Applications

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Abstract. It is widely believed, that the expressivity of STRIPS and STRIPS-like planning based on actions is generally lower than the expressivity of Hierarchical Task Network (HTN) and HTN-like planning, based on hierarchical decomposition. This would mean that a HTN-like planner can generally solve more domains than a STRIPS-like planner with the same extensions. In this paper, we show that both approaches, as they are practically used, are identically expressive and can solve all domains solvable by a Turing machine with finite tape (i.e. solvable by a common computer).

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Section: Expressivitymentioning

confidence: 99%

Section: Expressivitymentioning

confidence: 99%

“…In practice, modifications are used, restricting the plan space to finite and making the problem decidable [2].…”

Section: Expressivitymentioning

confidence: 99%

Section: Expressivitymentioning

confidence: 99%

“…This question was answered positively in the past [2]. The proof was, however, based on the assumption, that the HTN planner can use an infinite set of symbols to mark the tasks.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Expressivity of STRIPS-Like and HTN-Like Planning

Lekavý

Návrat

2007

Agent and Multi-Agent Systems: Technologies and Applications

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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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Applications of parallel processing technologies in heuristic search planning: methodologies and experiments

Phan

Pontelli

Son

et al. 2009

Concurrency and Computation

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SUMMARYThe goal of this paper is to investigate the application of parallel programming techniques to boost the performance of heuristic search-based planning systems in various aspects. It shows that an appropriate parallelization of a sequential planning system often brings gain in performance and/or scalability. We start by describing general schemes for parallelizing the construction of a plan. We then discuss the applications of these techniques to two domain-independent heuristic search-based planners-a competitive conformant planner (CPA) and a state-of-the-art classical planner (FF). We present experimental results-on both shared memory and distributed memory platforms-which show that the performance improvements and scalability are obtained in both cases. Finally, we discuss the issues that should be taken into consideration when designing a parallel planning system and relate our work to the existing literature.

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Complexity results for HTN planning

Cited by 168 publications

References 7 publications

Expressivity of STRIPS-Like and HTN-Like Planning

Expressivity of STRIPS-Like and HTN-Like Planning

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

Applications of parallel processing technologies in heuristic search planning: methodologies and experiments

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