REINFORCEMENT LEARNING AND STOCHASTIC OPTIMIZATION Clearing the jungle of stochastic optimization Sequential decision problems, which consist of "decision, information, decision, information," are ubiquitous, spanning virtually every human activity ranging from business applications, health (personal and public health, and medical decision making), energy, the sciences, all fields of engineering, finance, and e-commerce. The diversity of applications attracted the attention of at least 15 distinct fields of research, using eight distinct notational systems which produced a vast array of analytical tools. A byproduct is that powerful tools developed in one c ..

Sequential decision problems arise in virtually every human process. They span finance, energy, transportation, health, e-commerce, and supply chains and include pure learning problems that arise in laboratory or field experiments. They even cover search algorithms to maximize uncertain functions. An important dimension of every problem setting is the need to make decisions in the presence of different forms of uncertainty and evolving information processes. br Warren B. Powell's work in sequential decision problems started in the 1980s and spanned rail, energy, health, finance, e-commerce, supply chain management, and even learning for materials science. His ..