We propose a new approach to reinforcement learning which combines least squares function approximation with policy iteration. Our method is model-free and completely off policy. ...
We have developed and integrated software agents with two educational groupware systems (TeamWave Workplace and FLE), using evolutionary prototyping and empiricalbased design as d...
Our LAMDAer team has won the PAKDD'06 Data Mining Competition (Open Category) Grand Champion. This report presents our solution to PAKDD'06 Data Mining Competition. Follo...
Yang Yu, De-Chuan Zhan, Xu-Ying Liu, Ming Li, Zhi-...
This paper discusses a novel distributed adaptive algorithm and representation used to construct populations of adaptive Web agents. These InfoSpiders browse networked information ...
We present a general approach to model selection and regularization that exploits unlabeled data to adaptively control hypothesis complexity in supervised learning tasks. The idea ...