—Reinforcement learning is a framework in which an agent can learn behavior without knowledge on a task or an environment by exploration and exploitation. Striking a balance betw...
Zhengqiao Ji, Q. M. Jonathan Wu, Maher A. Sid-Ahme...
Abstract. The optimization and design of two different types of photonic devices - a Fibre Bragg Grating and a Microstructured Polymer Optical Fibre is presented in light of multi...
Steven Manos, Leon Poladian, Peter J. Bentley, Mar...
Evolutionary and genetic algorithms (EAs and GAs) are quite successful randomized function optimizers. This success is mainly based on the interaction of different operators like ...
This paper presents an approach to learning an optimal behavioral parameterization in the framework of a Case-Based Reasoning methodology for autonomous navigation tasks. It is ba...
Pass Transistor Logic has attracted more and more interest during last years, since it has proved to be an attractive alternative to static CMOS designs with respect to area, perf...