In this paper, we investigate the use of parallelization in reinforcement learning (RL), with the goal of learning optimal policies for single-agent RL problems more quickly by us...
In this paper active mode observability is addressed for a class of discrete-time linear systems that may switch in an unknown and unpredictable way among different modes taken f...
Marco Baglietto, Giorgio Battistelli, Luca Scardov...
: We present efficient solutions for the non-contiguous linear placement of data-paths for reconfigurable fabrics. A strip-based architecture is assumed for the reconfigurable fabr...
Redundancy analysis (RA) is a versatile technique used to predict multivariate criterion variables from multivariate predictor variables. The reduced-rank feature of RA captures r...
Abstract. We investigate the effect of linear independence in the strategies of congestion games on the convergence time of best improvement sequences and on the pure Price of Anar...