Engine Control Systems (ECS) for automobiles have numerous variants for many manufactures and different markets. To improve development efficiency, exploiting ECS commonalities an...
Reinforcement learning algorithms that employ neural networks as function approximators have proven to be powerful tools for solving optimal control problems. However, their traini...
Recently, there has been increasing interest in the issues of cost-sensitive learning and decision making in a variety of applications of data mining. A number of approaches have ...
Product Distribution (PD) theory is a new framework for controlling Multi-Agent Systems (MAS’s). First we review one motivation of PD theory, as the information-theoretic extens...
FACTOR/AIM (AIM) is a simulation system designed specifically for use in manufacturing decision support. AIM has been successfully applied to engineering design, scheduling, and p...