Composition of Stochastic Transition Systems Based on Spans and Couplings

Conventional approaches for parallel composition of stochastic systems relate probability measures of the individual components in terms of product measures. Such approaches rely on the assumption that components interact stochastically independent, which might be too rigid for modeling real world systems. In this paper, we introduce a parallel-composition operator for stochastic transition systems that is based on couplings of probability measures and does not impose any stochastic assumptions. When composing systems within our framework, the intended dependencies between components can be determined by providing so-called spans and span couplings. We present a congruence result for our operator with respect to a standard notion of bisimilarity and develop a general theory for spans, exploiting deep results from descriptive set theory. As an application of our general approach, we propose a model for stochastic hybrid systems called stochastic hybrid motion automata

Decisiveness of Stochastic Systems and its Application to Hybrid Models (Full Version)

In [ABM07], Abdulla et al. introduced the concept of decisiveness, an interesting tool for lifting good properties of finite Markov chains to denumerable ones. Later, this concept was extended to more general stochastic transition systems (STSs), allowing the design of various verification algorithms for large classes of (infinite) STSs. We further improve the understanding and utility of decisiveness in two ways. First, we provide a general criterion for proving decisiveness of general STSs. This criterion, which is very natural but whose proof is rather technical, (strictly) generalizes all known criteria from the literature. Second, we focus on stochastic hybrid systems (SHSs), a stochastic extension of hybrid systems. We establish the decisiveness of a large class of SHSs and, under a few classical hypotheses from mathematical logic, we show how to decide reachability problems in this class, even though they are undecidable for general SHSs. This provides a decidable stochastic extension of o-minimal hybrid systems. [ABM07] Parosh A. Abdulla, Noomene Ben Henda, and Richard Mayr. 2007. Decisive Markov Chains. Log. Methods Comput. Sci. 3, 4 (2007).Comment: Full version of GandALF 2020 paper (arXiv:2001.04347v2), updated version of arXiv:2001.04347v1. 30 pages, 6 figure

Stochastic transition systems: bisimulation, logic, and composition

Cyber-physical systems and the Internet of Things raise various challenges concerning the modelling and analysis of large modular systems. Models for such systems typically require uncountable state and action spaces, samplings from continuous distributions, and non-deterministic choices over uncountable many alternatives. In this thesis we fo- cus on a general modelling formalism for stochastic systems called stochastic transition system. We introduce a novel composition operator for stochastic transition systems that is based on couplings of probability measures. Couplings yield a declarative modelling paradigm appropriate for the formalisation of stochastic dependencies that are caused by the interaction of components. Congruence results for our operator with respect to standard notions for simulation and bisimulation are presented for which the challenge is to prove the existence of appropriate couplings. In this context a theory for stochastic transition systems concerning simulation, bisimulation, and trace-distribution relations is developed. We show that under generic Souslin conditions, the simulation preorder is a subset of trace-distribution inclusion and accordingly, bisimulation equivalence is finer than trace-distribution equivalence. We moreover establish characterisations of the simulation preorder and the bisimulation equivalence for a broad subclass of stochastic transition systems in terms of expressive action-based probabilistic logics and show that these characterisations are still maintained by small fragments of these logics, respectively. To treat associated measurability aspects, we rely on methods from descriptive set theory, properties of Souslin sets, as well as prominent measurable-selection principles.:1 Introduction 2 Probability measures on Polish spaces 3 Stochastic transition systems 4 Simulations and trace distributions for Souslin systems 5 Action-based probabilistic temporal logics 6 Parallel composition based on spans and couplings 7 Relations to models from the literature 8 Conclusions 9 Bibliograph