Dynamic Programming

Dynamic Programming and Inventory Control: Volume 3 Studies in Probability, Optimization and Statistics (Repost)

A. Bensoussan, "Dynamic Programming and Inventory Control: Volume 3 Studies in Probability, Optimization and Statistics"
English | Sep 15, 2011 | ISBN: 1607507692 | 378 Pages | PDF | 1 MB

A Collection of Dynamic Programming Interview Questions Solved in C++  eBooks & eLearning

Posted by roxul at June 28, 2016
A Collection of Dynamic Programming Interview Questions Solved in C++

Dr Antonio Gulli, "A Collection of Dynamic Programming Interview Questions Solved in C++"
English | ISBN: 1495320480 | 2014 | 66 pages | EPUB | 1 MB

Dynamic Programming (Repost)  

Posted by DZ123 at Feb. 15, 2016
Dynamic Programming (Repost)

Richard Bellman, "Dynamic Programming"
English | 2003 | ISBN: 0486428095 | DJVU | pages: 365 | 4,1 mb

Reinforcement Learning and Approximate Dynamic Programming for Feedback Control  eBooks & eLearning

Posted by Grev27 at Nov. 22, 2015
Reinforcement Learning and Approximate Dynamic Programming for Feedback Control

Frank L. Lewis, Derong Liu, "Reinforcement Learning and Approximate Dynamic Programming for Feedback Control"
English | ISBN: 111810420X | 2012 | EPUB | 648 pages | 7,2 MB
Reinforcement Learning and Approximate Dynamic Programming for Feedback Control (Repost)

Reinforcement Learning and Approximate Dynamic Programming for Feedback Control By Frank L. Lewis, Derong Liu
2013 | 648 Pages | ISBN: 111810420X | PDF | 45 MB
Reinforcement Learning and Approximate Dynamic Programming for Feedback Control (repost)

Reinforcement Learning and Approximate Dynamic Programming for Feedback Control by Frank L. Lewis
English | Dec 26, 2012 | ISBN: 111810420X | 648 Pages | PDF | 44 MB

Reinforcement learning (RL) and adaptive dynamic programming (ADP) has been one of the most critical research fields in science and engineering for modern complex systems. This book describes the latest RL and ADP techniques for decision and control in human engineered systems, covering both single player decision and control and multi-player games.
Dynamic Programming and Inventory Control: Volume 3 Studies in Probability, Optimization and Statistics by A. Bensoussan

Dynamic Programming and Inventory Control: Volume 3 Studies in Probability, Optimization and Statistics by A. Bensoussan
English | Sep 15, 2011 | ISBN: 1607507692 | 378 Pages | PDF | 1 MB

This book presents a unified theory of dynamic programming and Markov decision processes and its application to a major field of operations research and operations management: inventory control. Models are developed in discrete time as well as in continuous time.
Stochastic Control Theory: Dynamic Programming Principle (2nd edition)

Makiko Nisio, "Stochastic Control Theory: Dynamic Programming Principle (2nd edition)"
2015 | ISBN-10: 4431551220 | 268 pages | PDF | 2 MB
Reinforcement Learning and Approximate Dynamic Programming for Feedback Control (repost)

Reinforcement Learning and Approximate Dynamic Programming for Feedback Control by Frank L. Lewis
English | Dec 26, 2012 | ISBN: 111810420X | 648 Pages | PDF | 44 MB

Reinforcement learning (RL) and adaptive dynamic programming (ADP) has been one of the most critical research fields in science and engineering for modern complex systems. This book describes the latest RL and ADP techniques for decision and control in human engineered systems, covering both single player decision and control and multi-player games. Edited by the pioneers of RL and ADP research, the book brings together ideas and methods from many fields and provides an important and timely guidance on controlling a wide variety of systems, such as robots, industrial processes, and economic decision-making.
Stochastic Dynamic Programming and the Control of Queueing Systems

Stochastic Dynamic Programming and the Control of Queueing Systems (Wiley Series in Probability and Statistics) by Linn I. Sennott
English | Sep 30, 1998 | ISBN: 0471161209 | 354 Pages | PDF | 17 MB

This book's clear presentation of theory, numerous chapter-end problems, and development of a unified method for the computation of optimal policies in both discrete and continuous time make it an excellent course text for graduate students and advanced undergraduates. Its comprehensive coverage of important recent advances in stochastic dynamic programming makes it a valuable working resource for operations research professionals, management scientists, engineers, and others.