On-the-fly PCTL fast mean-field approximated model-checking for self-organising coordination

On-the-fly Fast Mean-Field Model-Checking

A novel, scalable, on-the-fly model-checking procedure is presented to verify bounded PCTL properties of selected individuals in the context of very large systems of independent interacting objects. The proposed procedure combines on-the-fly model checking techniques with deterministic mean-field approximation in discrete time. The asymptotic correctness of the procedure is shown and some resul...

Design and Optimisation of the FlyFast Front-end for Attribute-based Coordination

Collective Adaptive Systems (CAS) consist of a large number of interacting objects. The design of such systems requires scalable analysis tools and methods, which have necessarily to rely on some form of approximation of the system’s actual behaviour. Promising techniques are those based on mean-field approximation. The FlyFast model-checker uses an on-the-fly algorithm for bounded PCTL model-c...

On-the-Fly Mean-Field Model-Checking for Attribute-Based Coordination

On-the-fly Probabilistic Model Checking

Model checking approaches can be divided into two broad categories: global approaches that determine the set of all states in a model M that satisfy a temporal logic formula Φ, and local approaches in which, given a state s in M , the procedure determines whether s satisfies Φ. When s is a term of a process language, the model-checking procedure can be executed “on-the-fly”, driven by the synta...

Exploiting Robust Optimization for Interval Probabilistic Bisimulation

Verification of PCTL properties of MDPs with convex uncertainties has been investigated recently by Puggelli et al. However, model checking algorithms typically suffer from the state space explosion problem. In this paper, we discuss the use of probabilistic bisimulation to reduce the size of such an MDP while preserving the PCTL properties it satisfies. As a core part, we show that deciding bi...