We show that states of a dynamical system can be usefully represented by multi-step, action-conditional predictions of future observations. State representations that are grounded...
Michael L. Littman, Richard S. Sutton, Satinder P....
Previous studies on mining sequential patterns have focused on temporal patterns specified by some form of propositional temporal logic. However, there are some interesting sequen...
Sandra de Amo, Daniel A. Furtado, Arnaud Giacomett...
In this paper, we propose a novel method to infer the web user’s Information Content (IC), which is the information that the user must examine to complete her task. In particula...
Inference is a key component in learning probabilistic models from partially observable data. When learning temporal models, each of the many inference phases requires a complete ...
This paper describes a new method for extracting open compounds (uninterrupted sequences of words) from text corpora of languages, such as Thai, Japanese and Korea that exhibit un...