In the paper, we investigate the use of reinforcement learning in CBR for estimating and managing a legacy case base for playing the game of Tetris. Each case corresponds to a loc...
In this paper a method for image segmentation using an opposition-based reinforcement learning scheme is introduced. We use this agent-based approach to optimally find the appropri...
For transmission of continuous media (CM) streams such as audio and video over the Internet, a critical issue is that periodic network overloads cause bursty packet losses. Studie...
We describe the Fourier Basis, a linear value function approximation scheme based on the Fourier Series. We empirically evaluate its properties, and demonstrate that it performs w...
Abstract. In this paper we present a Reinforcement Learning (RL) approach with the capability to train neural adaptive controllers for complex control problems without expensive on...