Markov Decision Processes in Practice - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Markov Decision Processes in Practice write by Richard J. Boucherie. This book was released on 2017-03-10. Markov Decision Processes in Practice available in PDF, EPUB and Kindle. This book presents classical Markov Decision Processes (MDP) for real-life applications and optimization. MDP allows users to develop and formally support approximate and simple decision rules, and this book showcases state-of-the-art applications in which MDP was key to the solution approach. The book is divided into six parts. Part 1 is devoted to the state-of-the-art theoretical foundation of MDP, including approximate methods such as policy improvement, successive approximation and infinite state spaces as well as an instructive chapter on Approximate Dynamic Programming. It then continues with five parts of specific and non-exhaustive application areas. Part 2 covers MDP healthcare applications, which includes different screening procedures, appointment scheduling, ambulance scheduling and blood management. Part 3 explores MDP modeling within transportation. This ranges from public to private transportation, from airports and traffic lights to car parking or charging your electric car . Part 4 contains three chapters that illustrates the structure of approximate policies for production or manufacturing structures. In Part 5, communications is highlighted as an important application area for MDP. It includes Gittins indices, down-to-earth call centers and wireless sensor networks. Finally Part 6 is dedicated to financial modeling, offering an instructive review to account for financial portfolios and derivatives under proportional transactional costs. The MDP applications in this book illustrate a variety of both standard and non-standard aspects of MDP modeling and its practical use. This book should appeal to readers for practitioning, academic research and educational purposes, with a background in, among others, operations research, mathematics, computer science, and industrial engineering.
Markov Decision Processes in Artificial Intelligence
Markov Decision Processes in Artificial Intelligence - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Markov Decision Processes in Artificial Intelligence write by Olivier Sigaud. This book was released on 2013-03-04. Markov Decision Processes in Artificial Intelligence available in PDF, EPUB and Kindle. Markov Decision Processes (MDPs) are a mathematical framework for modeling sequential decision problems under uncertainty as well as reinforcement learning problems. Written by experts in the field, this book provides a global view of current research using MDPs in artificial intelligence. It starts with an introductory presentation of the fundamental aspects of MDPs (planning in MDPs, reinforcement learning, partially observable MDPs, Markov games and the use of non-classical criteria). It then presents more advanced research trends in the field and gives some concrete examples using illustrative real life applications.
Handbook of Markov Decision Processes
Handbook of Markov Decision Processes - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Handbook of Markov Decision Processes write by Eugene A. Feinberg. This book was released on 2012-12-06. Handbook of Markov Decision Processes available in PDF, EPUB and Kindle. Eugene A. Feinberg Adam Shwartz This volume deals with the theory of Markov Decision Processes (MDPs) and their applications. Each chapter was written by a leading expert in the re spective area. The papers cover major research areas and methodologies, and discuss open questions and future research directions. The papers can be read independently, with the basic notation and concepts ofSection 1.2. Most chap ters should be accessible by graduate or advanced undergraduate students in fields of operations research, electrical engineering, and computer science. 1.1 AN OVERVIEW OF MARKOV DECISION PROCESSES The theory of Markov Decision Processes-also known under several other names including sequential stochastic optimization, discrete-time stochastic control, and stochastic dynamic programming-studiessequential optimization ofdiscrete time stochastic systems. The basic object is a discrete-time stochas tic system whose transition mechanism can be controlled over time. Each control policy defines the stochastic process and values of objective functions associated with this process. The goal is to select a "good" control policy. In real life, decisions that humans and computers make on all levels usually have two types ofimpacts: (i) they cost orsavetime, money, or other resources, or they bring revenues, as well as (ii) they have an impact on the future, by influencing the dynamics. In many situations, decisions with the largest immediate profit may not be good in view offuture events. MDPs model this paradigm and provide results on the structure and existence of good policies and on methods for their calculation.
Markov Decision Processes with Applications to Finance
Markov Decision Processes with Applications to Finance - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Markov Decision Processes with Applications to Finance write by Nicole Bäuerle. This book was released on 2011-06-06. Markov Decision Processes with Applications to Finance available in PDF, EPUB and Kindle. The theory of Markov decision processes focuses on controlled Markov chains in discrete time. The authors establish the theory for general state and action spaces and at the same time show its application by means of numerous examples, mostly taken from the fields of finance and operations research. By using a structural approach many technicalities (concerning measure theory) are avoided. They cover problems with finite and infinite horizons, as well as partially observable Markov decision processes, piecewise deterministic Markov decision processes and stopping problems. The book presents Markov decision processes in action and includes various state-of-the-art applications with a particular view towards finance. It is useful for upper-level undergraduates, Master's students and researchers in both applied probability and finance, and provides exercises (without solutions).
Markov Chains and Decision Processes for Engineers and Managers
Markov Chains and Decision Processes for Engineers and Managers - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Markov Chains and Decision Processes for Engineers and Managers write by Theodore J. Sheskin. This book was released on 2016-04-19. Markov Chains and Decision Processes for Engineers and Managers available in PDF, EPUB and Kindle. Recognized as a powerful tool for dealing with uncertainty, Markov modeling can enhance your ability to analyze complex production and service systems. However, most books on Markov chains or decision processes are often either highly theoretical, with few examples, or highly prescriptive, with little justification for the steps of the algorithms u
