Abstract. We present a new reinforcement learning approach for deterministic continuous control problems in environments with unknown, arbitrary reward functions. The difficulty of...
Abstract. In this paper, we propose a new framework for the parametric verification of time Petri nets with stopwatches controlled by inhibitor arcs. We first introduce an extensio...
Louis-Marie Traonouez, Didier Lime, Olivier H. Rou...
Abstract-- The need for efficient computation of approximate global state lies at the heart of a wide range of problems in distributed systems. Examples include routing in the Inte...
We propose a rule-based approach for transforming B abstract machines into UML diagrams. We believe that important insight into the structure underlying a B model can be gained by...
Abstract. In this paper we consider the problem of computing the density of states of a Boolean formula in CNF, a generalization of both MAX-SAT and model counting. Given a Boolean...