laboratoire IBISC, bat. IBGBI, 23 bd de France, Evry, amphi du rez-de-chaussée: comment y aller
Il est possible de garer sa voiture dans le parking souterrain en appelant la loge à partir de la borne d'entrée
Abstract : The dynamics of Boolean networks (BNs) is usually computed according to a fixed update mode (synchronous, asynchronous, etc.). However, update modes can miss important behaviours actually realisable in more concrete multilevel or quantitative models. We introduce the most permissive semantics of BNs which guarantees a correct over-approximation of behaviours of any multilevel refinement. Moreover, it turns out that analysing the most permissive dynamics of BNs is much simpler than with update modes: reachability is PTIME (instead of PSPACE-complete), and identifying attractors is NP (instead of PSPACE-complete). Therefore, computing reachable attractors become tractable to very large networks, without any assumption on their structure. We conclude on the impact for learning networks from time series data.
Abstract : Autonomous vehicle's behavioural analysis represents a major challenge in the automotive world. We propose an efficient formal modeling of a system of autonomous vehicles, in order to obtain guarantees of its good functioning and robustness. The inherent size of the system makes it impossible to address the problem in a direct and naive way, but a suitable discretization and approximation allows to use model checking exhaustive techniques while limiting the state explosion. This approach is complemented by simulation in order to check relevance of the results obtained on the approximated model.