Abstract. Reinforcement learning (RL) is a widely used learning paradigm for adaptive agents. There exist several convergent and consistent RL algorithms which have been intensivel...
Lucian Busoniu, Damien Ernst, Bart De Schutter, Ro...
Abstract. In this paper we present an action/state-based logical framework for the analysis and verification of complex systems, which relies on the definition of doubly labelled...
Maurice H. ter Beek, Alessandro Fantechi, Stefania...
Today’s module systems do not effectively support information hiding in the presence of shared mutable objects, causing serious problems in the development and evolution of larg...
Abstract. Many evolutionary algorithm applications involve either fitness functions with high time complexity or large dimensionality (hence very many fitness evaluations will typi...
Abstract. In the eld of reactive system programming, data ow synchronous languages like Lustre BCH+85,CHPP87 or Signal GBBG85 o er a syntax similar to block-diagrams, and can be e ...