For a Markov Decision Process with finite state (size S) and action spaces (size A per state), we propose a new algorithm--Delayed Q-Learning. We prove it is PAC, achieving near o...
Alexander L. Strehl, Lihong Li, Eric Wiewiora, Joh...
In this work we present a novel approach for learning nonhomogenous textures without facing the unlearning problem. Our learning method mimics the human behavior of selective lear...
Educational games have the potential to provide intrinsically motivating learning experiences that immerse and engage the learner. However, the much heralded benefits of education...
The focus of this paper is on student learning theory. Use is made of an "analytic discovery tool" called Quantitative CyberQuest (QCQ) to help conceptualize the many go...
Conversational Case-Based Reasoning (CCBR) provides a mixed-initiative dialog for guiding users to refine their problem descriptions incrementally through a question-answering seq...