With the increasing levels of variability and randomness in the characteristics and behavior of manufactured nanoscale structures and devices, achieving performance optimization u...
— Decision optimization is used in many applications such as those for finding the best course of action in emergencies. However, optimization solutions require considerable mat...
Alexander Brodsky, Nathan E. Egge, Xiaoyang Sean W...
Effective supply chain distribution network design needs to consider various performance dimensions and product characteristics. Recently, researchers have begun to realize that t...
We present an efficient "sparse sampling" technique for approximating Bayes optimal decision making in reinforcement learning, addressing the well known exploration vers...
Tao Wang, Daniel J. Lizotte, Michael H. Bowling, D...
To model combinatorial decision problems involving uncertainty and probability, we introduce stochastic constraint programming. Stochastic constraint programs contain both decision...