In this paper, we study an online make-to-order variant of the classical joint replenishment problem (JRP) that has been studied extensively over the years and plays a fundamental...
Learning in real-world domains often requires to deal with continuous state and action spaces. Although many solutions have been proposed to apply Reinforcement Learning algorithm...
Alessandro Lazaric, Marcello Restelli, Andrea Bona...
Dynamic Bayesian networks are structured representations of stochastic processes. Despite their structure, exact inference in DBNs is generally intractable. One approach to approx...
In this paper, we propose a novel algorithm for directional temporal texture synthesis. The generated temporal textures can move in any user-specified direction at run time, while...
In [7] Maria I. Sessa extended the SLD resolution principle with the ability of performing approximate reasoning and flexible query answering. The operational mechanism of similar...