3 results
Giorgio Bacci ; Giovanni Bacci ; Kim G. Larsen ; Radu Mardare.
We propose a distance between continuous-time Markov chains (CTMCs) and study the problem of computing it by comparing three different algorithmic methodologies: iterative, linear program, and on-the-fly. In a work presented at FoSSaCS'12, Chen et al. characterized the bisimilarity distance of […]
Published on June 30, 2017
Giorgio Bacci ; Giovanni Bacci ; Kim G. Larsen ; Radu Mardare ; Qiyi Tang ; Franck van Breugel.
The probabilistic bisimilarity distance of Deng et al. has been proposed as a robust quantitative generalization of Segala and Lynch's probabilistic bisimilarity for probabilistic automata. In this paper, we present a characterization of the bisimilarity distance as the solution of a simple […]
Published on February 3, 2021
Giorgio Bacci ; Giovanni Bacci ; Kim G. Larsen ; Radu Mardare.
In this paper we propose a complete axiomatization of the bisimilarity distance of Desharnais et al. for the class of finite labelled Markov chains. Our axiomatization is given in the style of a quantitative extension of equational logic recently proposed by Mardare, Panangaden, and Plotkin (LICS […]
Published on November 16, 2018