{"type":"ScholarlyArticle","title":"Solving QNP and FOND+ with Generating, Testing and Forbidding","authors":[{"name":"Zheyuan Shi","slug":"zheyuan-shi","given":"Zheyuan","family":"Shi","affiliation":""},{"name":"Hao Dong","slug":"hao-dong","given":"Hao","family":"Dong","affiliation":""},{"name":"Yongmei Liu","slug":"yongmei-liu","given":"Yongmei","family":"Liu","affiliation":""}],"abstract":"Qualitative Numerical Planning (QNP) extends classical planning with numerical variables that can be changed by arbitrary amounts. FOND+ extends Fully Observable Non-Deterministic (FOND) planning by introducing explicit fairness assumptions, resulting in a more expressive model that can also capture QNP as a special case. However, existing QNP and FOND+ solvers still face significant scalability challenges. To address this, we propose a novel framework for solving QNP and FOND+ by generating strong cyclic solutions of the associated FOND problem, testing their validity, and forbidding non-solutions in conducting further searches. For this, we propose a procedure called SIEVE*, which generalizes the QNP termination testing algorithm SIEVE to determine whether a strong cyclic solution is a FOND+ solution. Additionally, we propose several optimization techniques to further improve the performance of our basic framework. We implemented our approach based on the advanced FOND solver PRP; experimental results show that our solver shows superior scalability over the existing QNP and FOND+ solvers.","doi":"10.24963/ijcai.2025/961","url":"https://ijcai.org/proceedings/2025/961","pdf":"https://ijcai.org/proceedings/2025/0961.pdf","markdown":"https://ijcai.org/proceedings/2025/961.md","bibtex":"https://ijcai.org/proceedings/2025/bibtex/961","volume":{"slug":"2025","title":"Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2025","url":"https://ijcai.org/proceedings/2025/","year":2025,"location":"Montreal, Canada","dates":"16-22 August 2025","editors":"James Kwok","isbn":"978-1-956792-06-5","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2025"},"section":"Planning and Scheduling","track":"Main Track","number":961,"pages":{"first":8644,"last":8651},"keywords":["Planning and Scheduling: PS: Planning under uncertainty","Planning and Scheduling: PS: Planning algorithms"],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}