This paper summarizes research on a new emerging framework for learning to plan using the Markov decision process model (MDP). In this paradigm, two approaches to learning to plan...
Sridhar Mahadevan, Sarah Osentoski, Jeffrey Johns,...
While determining model complexity is an important problem in machine learning, many feature learning algorithms rely on cross-validation to choose an optimal number of features, ...
We describe our preliminary work in modeling conversation specifications and policies as positive/negative permissions and obligations. Our model is generic as it is independent o...
Several published reports show that instancebased learning algorithms yield high classification accuracies and have low storage requirements during supervised learning application...
This paper describes the CMU/InterACT effort in developing an Arabic Automatic Speech Recognition (ASR) system for broadcast news and conversations within the GALE 2006 evaluation...