Planning methods for deterministic planning problems traditionally exploit factored representations to encode the dynamics of problems in terms of a set of parameters, e.g., the l...
Simulation optimization is rapidly becoming a mainstream tool for simulation practitioners. Simulation optimization is the practice of linking an optimization method with a simula...
Abstract. The paper proposes a learning approach to support medical researchers in the context of in-vivo cancer imaging, and specifically in the analysis of Dynamic Contrast-Enhan...
Alessandro Daducci, Umberto Castellani, Marco Cris...
Many applications in multiagent learning are essentially convex optimization problems in which agents have only limited communication and partial information about the function be...
Renato L. G. Cavalcante, Alex Rogers, Nicholas R. ...
Abstract. This contribution studies speciation from the standpoint of evolutionary robotics (ER). A common approach to ER is to design a robot’s control system using neuro-evolut...