Planning Task Shielding: Detecting and Repairing Flaws in Planning Tasks through Turning them Unsolvable
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
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2026
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| _version_ | 1866911624875474944 |
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| author | Pozanco, Alberto Morales, Marianela Totis, Pietro Borrajo, Daniel |
| author_facet | Pozanco, Alberto Morales, Marianela Totis, Pietro Borrajo, Daniel |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_07042 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Planning Task Shielding: Detecting and Repairing Flaws in Planning Tasks through Turning them Unsolvable Pozanco, Alberto Morales, Marianela Totis, Pietro Borrajo, Daniel Artificial Intelligence 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. |
| title | Planning Task Shielding: Detecting and Repairing Flaws in Planning Tasks through Turning them Unsolvable |
| topic | Artificial Intelligence |
| url | https://arxiv.org/abs/2604.07042 |