A novel approach to integrating case-based reasoning with model-based diagnosis is presented. The main idea is to use the model of the device and the results of diagnostic tests t...
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,...
R-max is a very simple model-based reinforcement learning algorithm which can attain near-optimal average reward in polynomial time. In R-max, the agent always maintains a complet...
Student models for Intelligent Computer Assisted Language Learning (ICALL) have largely focused on the acquisition of grammatical structures. In this paper, we motivate a broader p...
One of the central problems in building broad-coverage story understanding systems is generating expectations about event sequences, i.e. predicting what happens next given some a...