We extend the classical system relations of trace inclusion, trace equivalence, simulation, and bisimulation to a quantitative setting in which propositions are interpreted not as boolean values, but as elements of arbitrary metric spaces. Trace inclusion and equivalence give rise to asymmetrical and symmetrical linear distances, while simulation and bisimulation give rise to asymmetrical and symmetrical branching distances. We study the relationships among these distances, and we provide a full logical characterization of the distances in terms of quantitative versions of LTL and mu-calculus. We show that, while trace inclusion (resp. equivalence) coincides with simulation (resp. bisimulation) for deterministic boolean transition systems, ...
We lay out a general method for computing branching distances between labeled transition systems. We...
International audienceWe present a distance-agnostic approach to quantitative verification. Taking a...
We present a distance-agnostic approach to quantitative verification. Taking as input an unspecified...
We extend the classical system relations of trace inclusion, trace equivalence, simulation, and bisi...
Abstract — We extend the classical system relations of trace inclusion, trace equivalence, simulatio...
We extend the basic system relations of trace inclusion, trace equivalence, simulation, and bisimula...
We extend the basic system relations of trace inclusion, trace equivalence, simulation, and bisimula...
International audienceWe develop a general framework for reasoning about distances between transitio...
We present a distance-agnostic approach to quantitative verification. Taking as input an unspecified...
AbstractSimulation distances are essentially approximations of simulation which provide a measure of...
Simulation distances are essentially approximations of simulation which provide a measure of the ext...
We introduce a general class of distances (metrics) between Markov chains, which are based on linear...
Abstract. We study the strong and strutter trace distances on Markov chains (MCs). Our interest in t...
We study the strong and strutter trace distances on Markov chains (MCs). Our interest in these metri...
Abstract. The formalism of metric transition systems, as introduced by de Alfaro, Faella and Stoelin...
We lay out a general method for computing branching distances between labeled transition systems. We...
International audienceWe present a distance-agnostic approach to quantitative verification. Taking a...
We present a distance-agnostic approach to quantitative verification. Taking as input an unspecified...
We extend the classical system relations of trace inclusion, trace equivalence, simulation, and bisi...
Abstract — We extend the classical system relations of trace inclusion, trace equivalence, simulatio...
We extend the basic system relations of trace inclusion, trace equivalence, simulation, and bisimula...
We extend the basic system relations of trace inclusion, trace equivalence, simulation, and bisimula...
International audienceWe develop a general framework for reasoning about distances between transitio...
We present a distance-agnostic approach to quantitative verification. Taking as input an unspecified...
AbstractSimulation distances are essentially approximations of simulation which provide a measure of...
Simulation distances are essentially approximations of simulation which provide a measure of the ext...
We introduce a general class of distances (metrics) between Markov chains, which are based on linear...
Abstract. We study the strong and strutter trace distances on Markov chains (MCs). Our interest in t...
We study the strong and strutter trace distances on Markov chains (MCs). Our interest in these metri...
Abstract. The formalism of metric transition systems, as introduced by de Alfaro, Faella and Stoelin...
We lay out a general method for computing branching distances between labeled transition systems. We...
International audienceWe present a distance-agnostic approach to quantitative verification. Taking a...
We present a distance-agnostic approach to quantitative verification. Taking as input an unspecified...