Decision-making to satisfy the basic human needs of health, food, and education is complex,
accomplishing this in such a way that solutions are personalized to the needs of the …

This chapter introduces the basics of Markov decision process (MDP) modeling through
motivating examples and examines the sorts of results that may be obtained using MDPs. It …

Medical treatment decisions are often sequential and uncertain. Markov decision processes
(MDPs) are an appropriate technique for modeling and solving such stochastic and dynamic …

Markov decision processes (MDPs) constitute one of the most general frameworks for
modeling decision-making under uncertainty, being used in multiple fields, including …

This dissertation employs management systems engineering principles, data science, and
industrial systems engineering techniques to address pressing challenges in emergency …

Medical decision making (MDM), the discipline applying systematic approaches to solve the
decision-making problems in healthcare, aims to develop standards for ideal decision …

● MDPs are a method for formulating and solving stochastic and dynamic decisions●
MDPs are very flexible, which is an advantage from a modeling perspective but a drawback …

When people ask–and provide resources–to develop a computational model of some
phenomena of interest, why do they do this? What are they expecting? How good are we at …

Events occur daily that challenge the health, security and sustainable growth of our society,
and often find us unprepared for the catastrophic outcomes. These events involve the …

Decision-theoretic systems, such as Markov Decision Processes (MDPs), are used for
sequential decision-making under uncertainty. MDPs provide a generic framework that can …