Abstract. Many heuristic estimators for classical planning are based on the socalled delete relaxation, which ignores negative effects of planning operators. Ideally, such heuristi...
Abstract. Feature selection in reinforcement learning (RL), i.e. choosing basis functions such that useful approximations of the unkown value function can be obtained, is one of th...
The goal of approximate policy evaluation is to “best” represent a target value function according to a specific criterion. Temporal difference methods and Bellman residual m...
—Considering process variability at the behavior synthesis level is necessary, because it makes some instances of function units slower and others faster, resulting in unbalanced...
— Thermal balancing and reducing hot-spots are two important challenges facing the MPSoC designers. In this work, we model the thermal behavior of a MPSoC as a control theory pro...
Francesco Zanini, David Atienza, Giovanni De Miche...