Beyond Nonexpansive Operations in Quantitative Algebraic Reasoning
| Autor: | Matteo Mio, Ralph Sarkis, Valeria Vignudelli |
|---|---|
| Přispěvatelé: | École normale supérieure de Lyon (ENS de Lyon), Preuves et Langages (PLUME), Laboratoire de l'Informatique du Parallélisme (LIP), École normale supérieure de Lyon (ENS de Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure de Lyon (ENS de Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS), ANR-20-CE48-0005,QuaReMe,Méthodes de raisonnement quantitative pour les logiques probabilistiques(2020) |
| Jazyk: | angličtina |
| Rok vydání: | 2022 |
| Předmět: | |
| Zdroj: | LICS '22: 37th Annual ACM/IEEE Symposium on Logic in Computer Science LICS '22: 37th Annual ACM/IEEE Symposium on Logic in Computer Science, Aug 2022, Haifa Israel, France. pp.1-13, ⟨10.1145/3531130.3533366⟩ |
| Popis: | The framework of quantitative equational logic has been successfully applied to reason about algebras whose carriers are metric spaces and operations are nonexpansive. We extend this framework in two orthogonal directions: algebras endowed with generalised metric space structures, and operations being nonexpansive up to a lifting. We apply our results to the algebraic axiomatisation of the {\L}ukaszyk--Karmowski distance on probability distributions, which has recently found application in the field of representation learning on Markov processes. |
| Databáze: | OpenAIRE |
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