In this paper, we propose a series of correlation-based feature selection methods for dealing with high dimensionality in feature-rich environments for modelbased Reinforcement Learning (RL). Real world RL tasks usually involve highdimensional feature spaces where standard RL methods often perform badly. Our proposed approach adopts correlation among state features as a selection criterion. The...

Effects such as student dropout and the non-normal distribution of duration data confound the exploration of tutor efficiency, time-intutor vs. tutor performance, in intelligent tutors. We use an accelerated failure time (AFT) model to analyze the effects of using automatically generated hints in Deep Thought, a propositional logic tutor. AFT is a branch of survival analysis, a statistical tech...

Editor’s note: This editorial is part of a series written by editors and co-authored with a senior executive, thought leader, or scholar to explore new content areas and grand challenges with the goal of expanding the scope, interestingness, and relevance of the work presented in the Academy of Management Journal. The principle is to use the editorial notes as “stage setters” to open up fresh, ...