Planning Task Shielding: Detecting and Repairing Flaws in Planning Tasks through Turning them Unsolvable

Computer Science > Artificial Intelligence [Submitted on 8 Apr 2026] Planning Task Shielding: Detecting and Repairing Flaws in Planning Tasks through Turning them Unsolvable Alberto Pozanco, Marianela Morales, Pietro Totis, Daniel Borrajo Most research in planning focuses on generating a plan to achieve a desired set of goals. However, a goal specification can also be used to encode a property that should never hold, allowing a planner to identify a trace that would reach a flawed state. In such cases, the objective may shift to modifying the planning task to ensure that the flawed state is never reached-in other words, to make the planning task unsolvable. In this paper we introduce planning task shielding: the problem of detecting and repairing flaws in planning tasks. We propose allmin, an optimal algorithm that solves these tasks by minimally modifying the original actions to render the planning task unsolvable. We empirically evaluate the performance of allmin in shielding planning tasks of increasing size, showing how it can effectively shield the system by turning the planning task unsolvable. Subjects: Artificial Intelligence (cs.AI) Cite as: arXiv:2604.07042 [cs.AI]   (or arXiv:2604.07042v1 [cs.AI] for this version)   https://doi.org/10.48550/arXiv.2604.07042 Focus to learn more Submission history From: Alberto Pozanco [view email] [v1] Wed, 8 Apr 2026 12:57:37 UTC (38 KB) Access Paper: HTML (experimental) view license Current browse context: cs.AI < prev   |   next > new | recent | 2026-04 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)