— High performance and compliant robot control requires accurate dynamics models which cannot be obtained analytically for sufficiently complex robot systems. In such cases, mac...
It has been observed that traditional decision trees produce poor probability estimates. In many applications, however, a probability estimation tree (PET) with accurate probabilit...
Predictive state representations (PSRs) are models that represent the state of a dynamical system as a set of predictions about future events. The existing work with PSRs focuses ...
Britton Wolfe, Michael R. James, Satinder P. Singh
We have developed a distributed DSS capable to working in a dynamic way. That is, when a domain of an organization needs a new kind of information, the system looks for this infor...
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. ...