In this paper we consider approximate policy-iteration-based reinforcement learning algorithms. In order to implement a flexible function approximation scheme we propose the use o...
Amir Massoud Farahmand, Mohammad Ghavamzadeh, Csab...
A new algorithm for on-line learning linear-threshold functions is proposed which efficiently combines second-order statistics about the data with the ”logarithmic behavior” ...
The evolution strategy is one of the strongest evolutionary algorithms for optimizing real-value vectors. In this paper, we study how to use it for the evolution of prediction wei...
Clustering aims to find useful hidden structures in data. In this paper we present a new clustering algorithm that builds upon the consistency method (Zhou, et.al., 2003), a semi-...