Download or read book Competitive Prices Dynamic Programming Under Uncertainty a Nonstationary Case written by Jack Schechtman and published by . This book was released on 1976 with total page 53 pages. Available in PDF, EPUB and Kindle. Book excerpt: A one-good economy is considered. The good can be used either for consumption or for production. If c units of the good are consumed and x units of the product are put into production, then the society gets u(t) (c) + p(t) (x) units of satisfaction, or utility, and the quantity of the good available in the next period is f(t) (x;w(t)) where w(t) are independent random variables. Using the concept of competitive prices and policies qualitative properties of optimal policies for finite and infinite time horizon problem are obtained. These results have applications to problem of nonrenewable resources, storage problem and economic growth models under uncertainty. (Author).

Download or read book Some Applications of Competitive Prices to Dynamic Programming Problems Under Uncertainty written by Jack Schechtman and published by . This book was released on 1973 with total page 68 pages. Available in PDF, EPUB and Kindle. Book excerpt: The author is concerned with a one-good economy. The good can be used at any period of time for production or consumption. If x units are put into production in period t then (f sup t) (x; (omega sup t)) units become available as outputs in period t + 1 ; where (omega sup t) is a random variable with known distribution. If c units are consumed in period t this produces (u sup t)(c) units of satisfaction or utility to the society in that period. The main interest is the study of qualitative properties of optimal solutions for a problem in which we maximize the total expected utility accumulated in t periods. (Author Modified Abstract).

Download or read book Annual Department of Defense Bibliography of Logistics Studies and Related Documents written by United States. Defense Logistics Studies Information Exchange and published by . This book was released on 1977 with total page 1200 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Approximate Dynamic Programming written by Warren B. Powell and published by John Wiley & Sons. This book was released on 2007-10-05 with total page 487 pages. Available in PDF, EPUB and Kindle. Book excerpt: A complete and accessible introduction to the real-world applications of approximate dynamic programming With the growing levels of sophistication in modern-day operations, it is vital for practitioners to understand how to approach, model, and solve complex industrial problems. Approximate Dynamic Programming is a result of the author's decades of experience working in large industrial settings to develop practical and high-quality solutions to problems that involve making decisions in the presence of uncertainty. This groundbreaking book uniquely integrates four distinct disciplines—Markov design processes, mathematical programming, simulation, and statistics—to demonstrate how to successfully model and solve a wide range of real-life problems using the techniques of approximate dynamic programming (ADP). The reader is introduced to the three curses of dimensionality that impact complex problems and is also shown how the post-decision state variable allows for the use of classical algorithmic strategies from operations research to treat complex stochastic optimization problems. Designed as an introduction and assuming no prior training in dynamic programming of any form, Approximate Dynamic Programming contains dozens of algorithms that are intended to serve as a starting point in the design of practical solutions for real problems. The book provides detailed coverage of implementation challenges including: modeling complex sequential decision processes under uncertainty, identifying robust policies, designing and estimating value function approximations, choosing effective stepsize rules, and resolving convergence issues. With a focus on modeling and algorithms in conjunction with the language of mainstream operations research, artificial intelligence, and control theory, Approximate Dynamic Programming: Models complex, high-dimensional problems in a natural and practical way, which draws on years of industrial projects Introduces and emphasizes the power of estimating a value function around the post-decision state, allowing solution algorithms to be broken down into three fundamental steps: classical simulation, classical optimization, and classical statistics Presents a thorough discussion of recursive estimation, including fundamental theory and a number of issues that arise in the development of practical algorithms Offers a variety of methods for approximating dynamic programs that have appeared in previous literature, but that have never been presented in the coherent format of a book Motivated by examples from modern-day operations research, Approximate Dynamic Programming is an accessible introduction to dynamic modeling and is also a valuable guide for the development of high-quality solutions to problems that exist in operations research and engineering. The clear and precise presentation of the material makes this an appropriate text for advanced undergraduate and beginning graduate courses, while also serving as a reference for researchers and practitioners. A companion Web site is available for readers, which includes additional exercises, solutions to exercises, and data sets to reinforce the book's main concepts.

Download or read book Operationalizing Dynamic Pricing Models written by Steffen Christ and published by Springer Science & Business Media. This book was released on 2011-04-02 with total page 363 pages. Available in PDF, EPUB and Kindle. Book excerpt: Steffen Christ shows how theoretic optimization models can be operationalized by employing self-learning strategies to construct relevant input variables, such as latent demand and customer price sensitivity.

Download or read book Measurement of Cost of Uncertainty in Stochastic Dynamic Programming Models written by A. S. Rajaraman and published by . This book was released on 1972 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Government reports annual index written by and published by . This book was released on 199? with total page 874 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Government Reports Announcements Index written by and published by . This book was released on 1993 with total page 1258 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Asset Pricing and Portfolio Choice Theory written by Kerry Back and published by Oxford University Press, USA. This book was released on 2010 with total page 504 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers the classical results on single-period, discrete-time, and continuous-time models of portfolio choice and asset pricing. It also treats asymmetric information, production models, various proposed explanations for the equity premium puzzle, and topics important for behavioral finance.

Download or read book Equilibrium Theory in Infinite Dimensional Spaces written by M. Ali Khan and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 441 pages. Available in PDF, EPUB and Kindle. Book excerpt: Apart from the underlying theme that all the contributions to this volume pertain to models set in an infinite dimensional space, they differ on many counts. Some were written in the early seventies while others are reports of ongoing research done especially with this volume in mind. Some are surveys of material that can, at least at this point in time, be deemed to have attained a satisfactory solution of the problem, while oth ers represent initial forays into an original and novel formulation. Some furnish alternative proofs of known, and by now, classical results, while others can be seen as groping towards and exploring formulations that have not yet reached a definitive form. The subject matter also has a wide leeway, ranging from solution concepts for economies to those for games and also including representation of preferences and discussion of purely mathematical problems, all within the rubric of choice variables belonging to an infinite dimensional space, interpreted as a commodity space or as a strategy space. Thus, this is a collective enterprise in a fairly wide sense of the term and one with the diversity of which we have interfered as little as possible. Our motivation for bringing all of this work under one set of covers was severalfold.

Download or read book Advances in Stochastic Dynamic Programming for Operations Management written by Frank Schneider and published by Logos Verlag Berlin GmbH. This book was released on 2014 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many tasks in operations management require the solution of complex optimization problems. Problems in which decisions are taken sequentially over time can be modeled and solved by dynamic programming. Real-world dynamic programming problems, however, exhibit complexity that cannot be handled by conventional solution techniques. This complexity may stem from large state and solution spaces, huge sets of possible actions, non-convexities in the objective function, and uncertainty. In this book, three highly complex real-world problems from the domain of operations management are modeled and solved by newly developed solution techniques based on stochastic dynamic programming. First, the problem of optimally scheduling participating demand units in an energy transmission network is considered. These units are scheduled such that total cost of supplying demand for electric energy is minimized under uncertainty in demand and generation. Second, the integrated problem of investment in and optimal operations of a network of battery swap stations under uncertain demand and energy prices is modeled and solved. Third, the inventory control problem of a multi-channel retailer selling through independent sales channels is modeled and optimality conditions for replenishment policies of simple structure are proven. This book introduces efficient approximation techniques based on approximate dynamic programming (ADP) and extends existing proximal point algorithms to the stochastic case. The methods are applicable to a wide variety of dynamic programming problems of high dimension.

Download or read book Reinforcement Learning and Dynamic Programming Using Function Approximators written by Lucian Busoniu and published by CRC Press. This book was released on 2017-07-28 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: From household appliances to applications in robotics, engineered systems involving complex dynamics can only be as effective as the algorithms that control them. While Dynamic Programming (DP) has provided researchers with a way to optimally solve decision and control problems involving complex dynamic systems, its practical value was limited by algorithms that lacked the capacity to scale up to realistic problems. However, in recent years, dramatic developments in Reinforcement Learning (RL), the model-free counterpart of DP, changed our understanding of what is possible. Those developments led to the creation of reliable methods that can be applied even when a mathematical model of the system is unavailable, allowing researchers to solve challenging control problems in engineering, as well as in a variety of other disciplines, including economics, medicine, and artificial intelligence. Reinforcement Learning and Dynamic Programming Using Function Approximators provides a comprehensive and unparalleled exploration of the field of RL and DP. With a focus on continuous-variable problems, this seminal text details essential developments that have substantially altered the field over the past decade. In its pages, pioneering experts provide a concise introduction to classical RL and DP, followed by an extensive presentation of the state-of-the-art and novel methods in RL and DP with approximation. Combining algorithm development with theoretical guarantees, they elaborate on their work with illustrative examples and insightful comparisons. Three individual chapters are dedicated to representative algorithms from each of the major classes of techniques: value iteration, policy iteration, and policy search. The features and performance of these algorithms are highlighted in extensive experimental studies on a range of control applications. The recent development of applications involving complex systems has led to a surge of interest in RL and DP methods and the subsequent need for a quality resource on the subject. For graduate students and others new to the field, this book offers a thorough introduction to both the basics and emerging methods. And for those researchers and practitioners working in the fields of optimal and adaptive control, machine learning, artificial intelligence, and operations research, this resource offers a combination of practical algorithms, theoretical analysis, and comprehensive examples that they will be able to adapt and apply to their own work. Access the authors' website at www.dcsc.tudelft.nl/rlbook/ for additional material, including computer code used in the studies and information concerning new developments.

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.

Download or read book Innovation Communication and Engineering written by Teen-Hang Meen and published by CRC Press. This book was released on 2013-10-08 with total page 2334 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume represents the proceedings of the 2013 International Conference on Innovation, Communication and Engineering (ICICE 2013). This conference was organized by the China University of Petroleum (Huadong/East China) and the Taiwanese Institute of Knowledge Innovation, and was held in Qingdao, Shandong, P.R. China, October 26 - November 1, 2013. The conference received 653 submitted papers from 10 countries, of which 214 papers were selected by the committees to be presented at ICICE 2013. The conference provided a unified communication platform for researchers in a wide range of fields from information technology, communication science, and applied mathematics, to computer science, advanced material science, design and engineering. This volume enables interdisciplinary collaboration between science and engineering technologists in academia and industry as well as networking internationally. Consists of a book of abstracts (260 pp.) and a USB flash card with full papers (912 pp.).

Download or read book Reinforcement Learning second edition written by Richard S. Sutton and published by MIT Press. This book was released on 2018-11-13 with total page 549 pages. Available in PDF, EPUB and Kindle. Book excerpt: The significantly expanded and updated new edition of a widely used text on reinforcement learning, one of the most active research areas in artificial intelligence. Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives while interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the field's key ideas and algorithms. This second edition has been significantly expanded and updated, presenting new topics and updating coverage of other topics. Like the first edition, this second edition focuses on core online learning algorithms, with the more mathematical material set off in shaded boxes. Part I covers as much of reinforcement learning as possible without going beyond the tabular case for which exact solutions can be found. Many algorithms presented in this part are new to the second edition, including UCB, Expected Sarsa, and Double Learning. Part II extends these ideas to function approximation, with new sections on such topics as artificial neural networks and the Fourier basis, and offers expanded treatment of off-policy learning and policy-gradient methods. Part III has new chapters on reinforcement learning's relationships to psychology and neuroscience, as well as an updated case-studies chapter including AlphaGo and AlphaGo Zero, Atari game playing, and IBM Watson's wagering strategy. The final chapter discusses the future societal impacts of reinforcement learning.

Download or read book International Journal of Production Economics written by and published by . This book was released on 2001 with total page 846 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Mobile Applications and Knowledge Advancements in E Business written by Lee, In and published by IGI Global. This book was released on 2012-08-31 with total page 419 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book covers emerging e-business theories, architectures, and technologies that are emphasized to stimulate and disseminate cutting-edge information into research and business communities in a timely fashion"--Provided by publisher.