Abstract
We introduce Modular Markovian Logic (MML) for compositional continuous-time and continuous-space Markov processes. MML combines operators specific to stochastic logics with operators reflecting the modular structure of the models, similar to those used by spatial and separation logics. We present a complete Hilbert-style axiomatization for MML, prove the small model property and analyze the relation between stochastic bisimulation and logical equivalence. © 2011 Springer-Verlag.
Cite
CITATION STYLE
Cardelli, L., Larsen, K. G., & Mardare, R. (2011). Modular Markovian logic. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6756 LNCS, pp. 380–391). https://doi.org/10.1007/978-3-642-22012-8_30
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.
