Amvik eBook Solutions

In this thesis, we study three classes of problems within the general area of sequential decision making with limited information, namely (i) sequential model-b

An introduction to decision making under uncertainty from a computational perspective, covering both theory and applications ranging from speech recognition to

A broad introduction to algorithms for decision making under uncertainty, introducing the underlying mathematical problem formulations and the algorithms for so

REINFORCEMENT LEARNING AND STOCHASTIC OPTIMIZATION Clearing the jungle of stochastic optimization Sequential decision problems, which consist of “decision, in

Control problems offer an industrially important application and a guide to understanding control systems for those working in Neural Networks. Neural Systems f