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Planning Domain Repair Using Preferred Plans and Background Knowledge

Authors Thomas Eckstein, Gerald Steinbauer-Wagner

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OASIcs.DX.2026.10.pdf
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  • 22 pages

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Subject Classification

ACM Subject Classification
  • Computing methodologies → Artificial intelligence
  • Computing methodologies → Planning and scheduling
Keywords
  • Planning
  • Planning Domain Definition Language (PDDL)
  • Debugging
  • Preferred Plans
  • Background Knowledge

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Abstract

Planning domain repair assists developers with the tedious task of finding and fixing errors in planning domains. We present Domain Repair for PDDL (DrPDDL), a novel automated debugger supporting lifted STRIPS domains with typing. As input, it takes a faulty domain, problem instances with corresponding preferred plans - plans the user desires but which may be invalid in the current domain - and optional State Integrity Axioms (SIAs) that must hold across all reachable states. Unlike prior tools, DrPDDL can also repair domains when the preferred plans are already valid. The debugger uses a pipeline of consecutive algorithms. It first relaxes the domain to fix failing action preconditions and SIA violations, and subsequently constricts it as much as possible while ensuring preferred plan validity. DrPDDL can add or remove positive and negative effects, as well as positive preconditions. We evaluated our debugger by automatically inserting random errors into International Planning Competition domains, generating thousands of test instances. The results demonstrate that DrPDDL successfully detects and repairs a high percentage of these errors.

Cite As Get BibTex

Thomas Eckstein and Gerald Steinbauer-Wagner. Planning Domain Repair Using Preferred Plans and Background Knowledge. In 37th International Conference on Principles of Diagnosis and Resilient Systems (DX 2026). Open Access Series in Informatics (OASIcs), Volume 148, pp. 10:1-10:22, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026) https://doi.org/10.4230/OASIcs.DX.2026.10

Author Details

Thomas Eckstein
  • Institute of Software Engineering and Artificial Intelligence, Graz University of Technology, Austria
Gerald Steinbauer-Wagner
  • Institute of Software Engineering and Artificial Intelligence, Graz University of Technology, Austria

References

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