—A generic approach that allows extracting functional nonlinear dependencies and mappings between atmospheric or ocean state variables in a relatively simple form is presented. T...
Vladimir M. Krasnopolsky, Carlos J. Lozano, Deanna...
Agent-based modeling, simulation, and network analysis approaches are one of the emergent techniques among soft computing literature. This paper presents an agent-based model for a...
Abstract. Learning to act in an unknown partially observable domain is a difficult variant of the reinforcement learning paradigm. Research in the area has focused on model-free m...
Modelling complex concurrent systems is often difficult and error-prone, in particular when new concepts coming from advanced practical applications are considered. These new appl...
Different solvers for computationally difficult problems such as satisfiability (SAT) perform best on different instances. Algorithm portfolios exploit this phenomenon by predicti...