Abstract
This paper presents a retrospective view on probabilistic model checking. We focus on Markov decision processes (MDPs, for short). We survey the basic ingredients of MDP model checking and discuss its enormous developments since the seminal works by Courcoubetis and Yannakakis in the early 1990s. We discuss in particular the manifold facets of this field of research by surveying the verification of various MDP extensions, rich classes of properties, and their applications.
Cite
CITATION STYLE
Baier, C., Hermanns, H., & Katoen, J. P. (2019). The 10,000 facets of mdp model checking. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10000, pp. 420–451). Springer. https://doi.org/10.1007/978-3-319-91908-9_21
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.
