A constrained approximate dynamic programming (ADP) approach is presented for designing adaptive neural network (NN) controllers with closed-loop stability and performance guarante...
A probabilistic wavelet system (PWS) is proposed to model the unknown dynamic system with stochastic and incomplete data. When compared with the traditional wavelet system, the PWS...
This paper describes several ensemble methods that combine multiple different reinforcement learning (RL) algorithms in a single agent. The aim is to enhance learning speed and fin...
Abstract--Network intrusion detection aims at distinguishing the attacks on the Internet from normal use of the Internet. It is an indispensable part of the information security sy...
Abstract--We present a real-time incremental approach to motion segmentation operating on sparse feature points. In contrast to previous work, the algorithm allows for a variable n...
In genetic programming (GP), evolving tree nodes separately would reduce the huge solution space. However, tree nodes are highly interdependent with respect to their fitness. In th...
Gang Li, Jin Feng Wang, Kin-Hong Lee, Kwong-Sak Le...
The paper examines characteristics of interactive learning between human tutors and a robot having a dynamic neural network model which is inspired by human parietal cortex functio...
Jun Tani, Ryunosuke Nishimoto, Jun Namikawa, Masat...
Sensor networks are widely used in monitoring and tracking a large number of objects. Without prior knowledge on the dynamics of object distribution, their density estimation could...
This correspondence presents an approach to the detection and isolation of component failures in large-scale systems. In the case of sensors that report at rates of 1 Hz or less, t...
Ozgur Erdinc, Craig Brideau, Peter Willett, Thiaga...