Optimal Decisions Under Uncertainty

Author : Mykel J. Kochenderfer
Publisher : MIT Press
ISBN 13 : 0262331713
Total Pages : 350 pages
Book Rating : 4.15/5 ( download)

DOWNLOAD NOW!

Download or read book Decision Making Under Uncertainty written by Mykel J. Kochenderfer and published by MIT Press. This book was released on 2015-07-24 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to decision making under uncertainty from a computational perspective, covering both theory and applications ranging from speech recognition to airborne collision avoidance. Many important problems involve decision making under uncertainty—that is, choosing actions based on often imperfect observations, with unknown outcomes. Designers of automated decision support systems must take into account the various sources of uncertainty while balancing the multiple objectives of the system. This book provides an introduction to the challenges of decision making under uncertainty from a computational perspective. It presents both the theory behind decision making models and algorithms and a collection of example applications that range from speech recognition to aircraft collision avoidance. Focusing on two methods for designing decision agents, planning and reinforcement learning, the book covers probabilistic models, introducing Bayesian networks as a graphical model that captures probabilistic relationships between variables; utility theory as a framework for understanding optimal decision making under uncertainty; Markov decision processes as a method for modeling sequential problems; model uncertainty; state uncertainty; and cooperative decision making involving multiple interacting agents. A series of applications shows how the theoretical concepts can be applied to systems for attribute-based person search, speech applications, collision avoidance, and unmanned aircraft persistent surveillance. Decision Making Under Uncertainty unifies research from different communities using consistent notation, and is accessible to students and researchers across engineering disciplines who have some prior exposure to probability theory and calculus. It can be used as a text for advanced undergraduate and graduate students in fields including computer science, aerospace and electrical engineering, and management science. It will also be a valuable professional reference for researchers in a variety of disciplines.

Author : Svetlana Boyarchenko
Publisher : Springer Science & Business Media
ISBN 13 : 3540737464
Total Pages : 292 pages
Book Rating : 4.69/5 ( download)

DOWNLOAD NOW!

Download or read book Irreversible Decisions under Uncertainty written by Svetlana Boyarchenko and published by Springer Science & Business Media. This book was released on 2007-08-26 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: Here, two highly experienced authors present an alternative approach to optimal stopping problems. The basic ideas and techniques of the approach can be explained much simpler than the standard methods in the literature on optimal stopping problems. The monograph will teach the reader to apply the technique to many problems in economics and finance, including new ones. From the technical point of view, the method can be characterized as option pricing via the Wiener-Hopf factorization.

Author : Jatikumar Sengupta
Publisher : Springer
ISBN 13 : 9780387108698
Total Pages : 0 pages
Book Rating : 4.96/5 ( download)

DOWNLOAD NOW!

Download or read book Optimal Decisions Under Uncertainty written by Jatikumar Sengupta and published by Springer. This book was released on 1981 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Author : J.K. Sengupta
Publisher : Springer Science & Business Media
ISBN 13 : 3642701639
Total Pages : 295 pages
Book Rating : 4.34/5 ( download)

DOWNLOAD NOW!

Download or read book Optimal Decisions Under Uncertainty written by J.K. Sengupta and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 295 pages. Available in PDF, EPUB and Kindle. Book excerpt: Understanding the stochastic enviornment is as much important to the manager as to the economist. From production and marketing to financial management, a manager has to assess various costs imposed by uncertainty. The economist analyzes the role of incomplete and too often imperfect information structures on the optimal decisions made by a firm. The need for understanding the role of uncertainty in quantitative decision models, both in economics and management science provide the basic motivation of this monograph. The stochastic environment is analyzed here in terms of the following specific models of optimization: linear and quadratic models, linear programming, control theory and dynamic programming. Uncertainty is introduced here through the para meters, the constraints, and the objective function and its impact evaluated. Specifically recent developments in applied research are emphasized, so that they can help the decision-maker arrive at a solution which has some desirable charac teristics like robustness, stability and cautiousness. Mathematical treatment is kept at a fairly elementary level and applied as pects are emphasized much more than theory. Moreover, an attempt is made to in corporate the economic theory of uncertainty into the stochastic theory of opera tions research. Methods of optimal decision rules illustrated he re are applicable in three broad areas: (a) applied economic models in resource allocation and economic planning, (b) operations research models involving portfolio analysis and stochastic linear programming and (c) systems science models in stochastic control and adaptive behavior.

Author : J. K. Sengupta
Publisher :
ISBN 13 : 9783642701641
Total Pages : 300 pages
Book Rating : 4.47/5 ( download)

DOWNLOAD NOW!

Download or read book Optimal Decisions Under Uncertainty written by J. K. Sengupta and published by . This book was released on 1985-01-01 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Author : J K Sengupta
Publisher :
ISBN 13 : 9783642877216
Total Pages : 172 pages
Book Rating : 4.14/5 ( download)

DOWNLOAD NOW!

Download or read book Optimal Decisions Under Uncertainty written by J K Sengupta and published by . This book was released on 1981-09-01 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Author : Joe Lorkowski
Publisher : Springer
ISBN 13 : 3319622145
Total Pages : 167 pages
Book Rating : 4.49/5 ( download)

DOWNLOAD NOW!

Download or read book Bounded Rationality in Decision Making Under Uncertainty: Towards Optimal Granularity written by Joe Lorkowski and published by Springer. This book was released on 2017-07-01 with total page 167 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book addresses an intriguing question: are our decisions rational? It explains seemingly irrational human decision-making behavior by taking into account our limited ability to process information. It also shows with several examples that optimization under granularity restriction leads to observed human decision-making. Drawing on the Nobel-prize-winning studies by Kahneman and Tversky, researchers have found many examples of seemingly irrational decisions: e.g., we overestimate the probability of rare events. Our explanation is that since human abilities to process information are limited, we operate not with the exact values of relevant quantities, but with “granules” that contain these values. We show that optimization under such granularity indeed leads to observed human behavior. In particular, for the first time, we explain the mysterious empirical dependence of betting odds on actual probabilities. This book can be recommended to all students interested in human decision-making, to researchers whose work involves human decisions, and to practitioners who design and employ systems involving human decision-making —so that they can better utilize our ability to make decisions under uncertainty.

Author : Antonio J. Conejo
Publisher : Springer Science & Business Media
ISBN 13 : 1441974210
Total Pages : 549 pages
Book Rating : 4.11/5 ( download)

DOWNLOAD NOW!

Download or read book Decision Making Under Uncertainty in Electricity Markets written by Antonio J. Conejo and published by Springer Science & Business Media. This book was released on 2010-09-08 with total page 549 pages. Available in PDF, EPUB and Kindle. Book excerpt: Decision Making Under Uncertainty in Electricity Markets provides models and procedures to be used by electricity market agents to make informed decisions under uncertainty. These procedures rely on well established stochastic programming models, which make them efficient and robust. Particularly, these techniques allow electricity producers to derive offering strategies for the pool and contracting decisions in the futures market. Retailers use these techniques to derive selling prices to clients and energy procurement strategies through the pool, the futures market and bilateral contracting. Using the proposed models, consumers can derive the best energy procurement strategies using the available trading floors. The market operator can use the techniques proposed in this book to clear simultaneously energy and reserve markets promoting efficiency and equity. The techniques described in this book are of interest for professionals working on energy markets, and for graduate students in power engineering, applied mathematics, applied economics, and operations research.

Author : Yuanguo Zhu
Publisher : Springer
ISBN 13 : 9811321345
Total Pages : 208 pages
Book Rating : 4.44/5 ( download)

DOWNLOAD NOW!

Download or read book Uncertain Optimal Control written by Yuanguo Zhu and published by Springer. This book was released on 2018-08-29 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces the theory and applications of uncertain optimal control, and establishes two types of models including expected value uncertain optimal control and optimistic value uncertain optimal control. These models, which have continuous-time forms and discrete-time forms, make use of dynamic programming. The uncertain optimal control theory relates to equations of optimality, uncertain bang-bang optimal control, optimal control with switched uncertain system, and optimal control for uncertain system with time-delay. Uncertain optimal control has applications in portfolio selection, engineering, and games. The book is a useful resource for researchers, engineers, and students in the fields of mathematics, cybernetics, operations research, industrial engineering, artificial intelligence, economics, and management science.

Author : Jonas Ekblom
Publisher : Linköping University Electronic Press
ISBN 13 : 9176852024
Total Pages : 36 pages
Book Rating : 4.26/5 ( download)

DOWNLOAD NOW!

Download or read book Decision Making under Uncertainty in Financial Markets written by Jonas Ekblom and published by Linköping University Electronic Press. This book was released on 2018-09-13 with total page 36 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis addresses the topic of decision making under uncertainty, with particular focus on financial markets. The aim of this research is to support improved decisions in practice, and related to this, to advance our understanding of financial markets. Stochastic optimization provides the tools to determine optimal decisions in uncertain environments, and the optimality conditions of these models produce insights into how financial markets work. To be more concrete, a great deal of financial theory is based on optimality conditions derived from stochastic optimization models. Therefore, an important part of the development of financial theory is to study stochastic optimization models that step-by-step better capture the essence of reality. This is the motivation behind the focus of this thesis, which is to study methods that in relation to prevailing models that underlie financial theory allow additional real-world complexities to be properly modeled. The overall purpose of this thesis is to develop and evaluate stochastic optimization models that support improved decisions under uncertainty on financial markets. The research into stochastic optimization in financial literature has traditionally focused on problem formulations that allow closed-form or `exact' numerical solutions; typically through the application of dynamic programming or optimal control. The focus in this thesis is on two other optimization methods, namely stochastic programming and approximate dynamic programming, which open up opportunities to study new classes of financial problems. More specifically, these optimization methods allow additional and important aspects of many real-world problems to be captured. This thesis contributes with several insights that are relevant for both financial and stochastic optimization literature. First, we show that the modeling of several real-world aspects traditionally not considered in the literature are important components in a model which supports corporate hedging decisions. Specifically, we document the importance of modeling term premia, a rich asset universe and transaction costs. Secondly, we provide two methodological contributions to the stochastic programming literature by: (i) highlighting the challenges of realizing improved decisions through more stages in stochastic programming models; and (ii) developing an importance sampling method that can be used to produce high solution quality with few scenarios. Finally, we design an approximate dynamic programming model that gives close to optimal solutions to the classic, and thus far unsolved, portfolio choice problem with constant relative risk aversion preferences and transaction costs, given many risky assets and a large number of time periods.