HTN Plan Repair Algorithms Compared: Strengths and Weaknesses of Different Methods

This paper provides theoretical and empirical comparisons of three recent hierarchical plan repair algorithms: SHOPFIXER, IPYHOPPER, and REWRITE. Our theoretical results show that the three algorithms correspond to three different definitions of the plan repair problem, leading to differences in the algorithms’ search spaces, the repair problems they can solve, and the kinds of repairs they can make. Understanding these distinctions is important when choosing a repair method for any given application. Building on the theoretical results, we evaluate the algorithms empirically in a series of benchmark planning problems. Our empirical results provide more detailed insight into the run- time repair performance of these systems and the coverage of the repair problems solved, based on algorithmic properties such as replanning, chronological backtracking, and back- jumping over plan trees.

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Publication Details

Journal
Proceedings of the International Conference on Automated Planning and Scheduling
Published
2025-09-16
DOI
https://doi.org/10.1609/icaps.v35i1.36131
Primary Topic
Parallel Computing and Optimization Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

HTN Plan Repair Algorithms Compared: Strengths and Weaknesses of Different Methods

Robert P. Goldman, Mark S. Roberts, Ugur Kuter, Dana Nau et al.
Proceedings of the International Conference on Automated Planning and Scheduling
Parallel Computing and Optimization Techniques
article

HTN Plan Repair Algorithms Compared: Strengths and Weaknesses of Different Methods

Robert P. Goldman, Mark S. Roberts, Ugur Kuter, Dana Nau, Paul Zaidins
article en

Abstract

This paper provides theoretical and empirical comparisons of three recent hierarchical plan repair algorithms: SHOPFIXER, IPYHOPPER, and REWRITE. Our theoretical results show that the three algorithms correspond to three different definitions of the plan repair problem, leading to differences in the algorithms’ search spaces, the repair problems they can solve, and the kinds of repairs they can make. Understanding these distinctions is important when choosing a repair method for any given application. Building on the theoretical results, we evaluate the algorithms empirically in a series of benchmark planning problems. Our empirical results provide more detailed insight into the run- time repair performance of these systems and the coverage of the repair problems solved, based on algorithmic properties such as replanning, chronological backtracking, and back- jumping over plan trees.

Proceedings of the International Conference on Automated Planning and SchedulingVol. 35(1)
United States Naval Research Laboratory (US), Institute for Systems Biology (US), Smart Information Flow Technologies (United States) (US)
Office of Naval Research, Air Force Research Laboratory
Openalex Percentile: Top 73%
Parallel Computing and Optimization Techniques
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HTN Plan Repair Algorithms Compared: Strengths and Weaknesses of Different Methods — Robert P. Goldman, Mark S. Roberts, et al. · Proceedings of the International Conference on Automated Planning and Scheduling (2025) | TGRS Research Map | TGRS