Reinforcement Learning (RL) is analyzed here as a tool for control system optimization. State and action spaces are assumed to be continuous. Time is assumed to be discrete, yet th...
Normal fuzzy CMAC neural network performs well because of its fast learning speed and local generalization capability for approximating nonlinear functions. However, it requires hu...
Floriberto Ortiz Rodriguez, Wen Yu, Marco A. Moren...
Scientists are increasingly utilizing Grids to manage large data sets and execute scientific experiments on distributed resources. Scientific workflows are used as means for modeli...
During the past decade there have been significant advances in the field of Natural Language Processing (NLP) and, in particular, Information Extraction (IE) [2] which have fueled...
Kiyoshi Sudo, Amit Bagga, Lawrence O'Gorman, Jon L...
This paper will discuss some resource allocation methods that can tolerate forecast errors under the Budget-Based management infrastructure, BBQ, which is designed to offer end-to-...