Unified Planning: Modeling, manipulating and solving AI planning problems in Python
Automated planning is a branch of artificial intelligence aiming at finding a course of action that achieves specified goals, given a description of the initial state of a system and a model of possible actions. There are plenty of planning approaches working under different assumptions and with different features (e.g. classical, temporal, and numeric planning). When automated planning is used in practice, however, the set of required features is often initially unclear. The Unified Planning (UP) library addresses this issue by providing a feature-rich Python API for modeling automated planning problems, which are solved seamlessly by planning engines that specify the set of features they support. Once a problem is modeled, UP can automatically find engines that can solve it, based on the features used in the model. This greatly reduces the commitment to specific planning approaches and bridges the gap between planning technology and its users.
Authors
- Sebastian Stock (ORCID: https://orcid.org/0000-0002-2231-8656)
- Uwe Köckemann (ORCID: https://orcid.org/0000-0001-7776-2116)
- Arthur Bit-Monnot (ORCID: https://orcid.org/0000-0003-0731-5796)
- Gabriele Röger (ORCID: https://orcid.org/0000-0002-0092-2107)
- Luca Iocchi (ORCID: https://orcid.org/0000-0001-9057-8946)
- Luigi Bonassi (ORCID: https://orcid.org/0000-0002-1783-8294)
- Andrea Micheli (ORCID: https://orcid.org/0000-0002-6370-1061)
- Enrico Scala (ORCID: https://orcid.org/0000-0003-2274-875X)
- Fabio Patrizi (ORCID: https://orcid.org/0000-0002-9116-251X)
- Alessandro Valentini (ORCID: https://orcid.org/0000-0001-5149-2090)
- Ivan Serina (ORCID: https://orcid.org/0000-0002-7785-9492)
- Alfonso Gerevini (ORCID: https://orcid.org/0000-0001-9008-6386)
- Félix Ingrand (ORCID: https://orcid.org/0000-0003-2822-0905)
- Alessandro Trapasso (ORCID: https://orcid.org/0000-0001-5431-6607)
- Alessandro Saetti (ORCID: https://orcid.org/0000-0002-2875-4459)
- Alberto Rovetta (ORCID: https://orcid.org/0009-0001-6224-1251)
- Luca Framba
Institutions
- Centre National de la Recherche Scientifique (FR)
- Université de Bretagne Occidentale (FR)
- Université Fédérale de Toulouse Midi-Pyrénées (FR)
- University of Basel (CH)
- Laboratoire d'Analyse et d'Architecture des Systèmes (FR)
- Institut National des Sciences Appliquées de Toulouse (FR)
- Fondazione Bruno Kessler (IT)
- Örebro University (SE)
- German Research Centre for Artificial Intelligence (DE)
- University of Brescia (IT)
- Sapienza University of Rome (IT)
Publication Details
- Journal
- SoftwareX
- Published
- 2024-12-19
- DOI
- https://doi.org/10.1016/j.softx.2024.102012
- Citations
- 12
- Primary Topic
- AI-based Problem Solving and Planning
- Type
- article
- Field-Weighted Citation Impact
- 4.17
Funders
- European Commission