We introduce new, efficient algorithms for value iteration with multiple reward functions and continuous state. We also give an algorithm for finding the set of all nondominated a...
Daniel J. Lizotte, Michael H. Bowling, Susan A. Mu...
We propose a model-based learning algorithm, the Adaptive Aggregation Algorithm (AAA), that aims to solve the online, continuous state space reinforcement learning problem in a de...
In this paper, we discuss the novel technology tagging and the results of analyzing a learning community in a popular system that relies on tagging namely YouTube. We present our ...
We study functions with multiple output values, and use active sampling to identify an example for each of the possible output values. Our results for this setting include: (1) Eff...
Language learning is a relatively new application for natural language processing (NLP) and for intelligent tutoring and learning environments (ITLEs). NLP has a crucial role to p...