—The functional heterogeneity of non-dedicated computational grids will increase with the inclusion of resources from desktop grids, P2P systems, and even mobile grids. Machine f...
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...
Task graph scheduling has been found effective in performance prediction and optimization of parallel applications. A number of static scheduling algorithms have been proposed for...
Distributed W-Learning (DWL) is a reinforcement learningbased algorithm for multi-policy optimization in agent-based systems. In this poster we propose the use of DWL for decentra...
In this paper, we present a full-system reconfigurable computing simulation platform intended to promote innovative new research in reconfigurable computing. Currently, reconfigur...