The proliferation of heterogeneous devices and diverse networking technologies demands flexible models to guarantee the quality-of-service(QoS) at the application session level, ...
Explanation-Based Reinforcement Learning (EBRL) was introduced by Dietterich and Flann as a way of combining the ability of Reinforcement Learning (RL) to learn optimal plans with...
Hybrid learning methods use theoretical knowledge of a domain and a set of classified examples to develop a method for classification. Methods that use domain knowledge have been ...
We present MBoost, a novel extension to AdaBoost that extends boosting to use multiple weak learners explicitly, and provides robustness to learning models that overfit or are po...
Accommodating learning styles in adaptive educational systems represents an important step towards providing individualized instruction. The paper summarizes the main results repo...