We consider the restless multi-armed bandit (RMAB) problem with unknown dynamics. In this problem, at each time, a player chooses K out of N (N > K) arms to play. The state of ...
It is well known that there cannot be a single "best" heuristic for optimal planning in general. One way of overcoming this is by combining admissible heuristics (e.g. b...
Semi-supervised inductive learning concerns how to learn a decision rule from a data set containing both labeled and unlabeled data. Several boosting algorithms have been extended...
In this paper, we present a new rule induction algorithm for machine learning in medical diagnosis. Medical datasets, as many other real-world datasets, exhibit an imbalanced clas...
This paper considers Just-In-Time Job-Shop Scheduling, in which each activity has an earliness and a tardiness cost with respect to a due date. It proposes a constraint programmin...