Abstract. We develop a way of analyzing the behavior of systems modeled using Discrete Time Markov Chains (DTMC). Specifically, we define iLTL, an LTL with linear inequalities on...
We present a generative model for representing and reasoning about the relationships among events in continuous time. We apply the model to the domain of networked and distributed...
This paper presents a new approach to inference in Bayesian networks. The principal idea is to encode the network by logical sentences and to compile the resulting encoding into an...
Systems of ordinary differential equations (ODEs) are often used to model the dynamics of complex biological pathways. We construct a discrete state model as a probabilistic appro...
This paper presents a modelling language, called MoDeST, for describing the behaviour of discrete event systems. The language combines conventional programming constructs – such ...
Pedro R. D'Argenio, Holger Hermanns, Joost-Pieter ...