Reinforcement learning is a paradigm under which an agent seeks to improve its policy by making learning updates based on the experiences it gathers through interaction with the en...
We present a visual analysis and exploration of fluid flow through a cooling jacket. Engineers invest a large amount of time and serious effort to optimize the flow through thi...
Robert S. Laramee, Christoph Garth, Helmut Doleisc...
The dynamic and lossy nature of wireless communication poses major challenges to reliable, self-organizing multihop networks. These non-ideal characteristics are more problematic ...
A major paradigm of modeling the decision making of autonomous agents is through behavior-based network models. The network consists of distributed behaviors that compete (or coop...
—This paper presents the design of an optimal Auxiliary Transient Neurocontroller (ATNC) for the Gate Controlled Series Capacitor (GCSC) in a multi-machine power system. GCSC is ...