Becker, ArvidCabalar, PedroDiéguez Lodeiro, MartínRomero Davila, JavierHahn, SusanaSchaub, Torsten2025-05-222025Becker, A., Cabalar, P., Diéguez, M., Hahn, S., Romero, J., Schaub, T. (2025). Compiling Metric Temporal Answer Set Programming. In: Dodaro, C., Gupta, G., Martinez, M.V. (eds) Logic Programming and Nonmonotonic Reasoning. LPNMR 2024. Lecture Notes in Computer Science(), vol 15245. Springer, Cham. https://doi.org/10.1007/978-3-031-74209-5_297830317420881611-33490302-9743http://hdl.handle.net/2183/42064Presented in the following conference: LPNMR 2024: 17th International Conference on Logic Programming and Nonmonotonic Reasoning, Dallas, TX, USA, October 11–14, 2024This version of the conference paper has been accepted for publication, after peer review; it is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: https://doi.org/10.1007/978-3-031-74209-5_2.[Abstract]: We develop a computational approach to Metric Answer Set Programming (ASP) to allow for expressing quantitative temporal constrains, like durations and deadlines. A central challenge is to maintain scalability when dealing with fine-grained timing constraints, which can significantly exacerbate ASP’s grounding bottleneck. To address this issue, we leverage extensions of ASP with difference constraints, a simplified form of linear constraints, to handle time-related aspects externally. Our approach effectively decouples metric ASP from the granularity of time, resulting in a solution that is unaffected by time precision.eng© 2025 Springer Nature Switzerland AG. This version is subject to Springer Nature’s AM terms of use - https://www.springernature.com/gp/open-research/policies/accepted-manuscript-termsAnswer set programmingComputational approachDifference constraintsFine grainedLinear constraintsTiming constraintsconference outputopen access10.1007/978-3-031-74209-5_2