By Warren B. Powell
Praise for the First Edition
"Finally, a booklet dedicated to dynamic programming and written utilizing the language of operations study (OR)! this pretty booklet fills a niche within the libraries of OR experts and practitioners."
This re-creation showcases a spotlight on modeling and computation for complicated sessions of approximate dynamic programming problems
Understanding approximate dynamic programming (ADP) is key with a purpose to strengthen functional and high quality options to complicated business difficulties, really while these difficulties contain making judgements within the presence of uncertainty. Approximate Dynamic Programming, moment variation uniquely integrates 4 detailed disciplines—Markov choice strategies, mathematical programming, simulation, and statistics—to exhibit tips to effectively method, version, and clear up quite a lot of real-life difficulties utilizing ADP.
The publication keeps to bridge the distance among laptop technology, simulation, and operations examine and now adopts the notation and vocabulary of reinforcement studying in addition to stochastic seek and simulation optimization. the writer outlines the fundamental algorithms that function a kick off point within the layout of useful options for genuine difficulties. the 3 curses of dimensionality that influence complicated difficulties are brought and distinctive insurance of implementation demanding situations is supplied. The Second Edition additionally features:*
A new bankruptcy describing 4 basic sessions of regulations for operating with assorted stochastic optimization difficulties: myopic regulations, look-ahead regulations, coverage functionality approximations, and regulations in line with worth functionality approximations*
A new bankruptcy on coverage seek that brings jointly stochastic seek and simulation optimization recommendations and introduces a brand new classification of optimum studying suggestions*
Updated insurance of the exploration exploitation challenge in ADP, now together with a lately built procedure for doing energetic studying within the presence of a actual nation, utilizing the concept that of the information gradient*
A new series of chapters describing statistical equipment for approximating price services, estimating the worth of a set coverage, and cost functionality approximation whereas trying to find optimum policies
The awarded insurance of ADP emphasizes types and algorithms, targeting similar functions and computation whereas additionally discussing the theoretical facet of the subject that explores proofs of convergence and price of convergence. A comparable web site good points an ongoing dialogue of the evolving fields of approximation dynamic programming and reinforcement studying, in addition to extra readings, software program, and datasets.
Requiring just a uncomplicated knowing of facts and chance, Approximate Dynamic Programming, moment version is a wonderful booklet for commercial engineering and operations examine classes on the upper-undergraduate and graduate degrees. It additionally serves as a useful reference for researchers and pros who make the most of dynamic programming, stochastic programming, and keep watch over conception to unravel difficulties of their daily paintings.
Read Online or Download Approximate Dynamic Programming: Solving the Curses of Dimensionality (2nd Edition) (Wiley Series in Probability and Statistics) PDF
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Additional info for Approximate Dynamic Programming: Solving the Curses of Dimensionality (2nd Edition) (Wiley Series in Probability and Statistics)
Index variables - Throughout, i, j, k, l, m and n are always scalar indices. Of course, there are exceptions to every rule. It is extremely common in the transportation literature to model the flow of a type of resource (called a commodity and indexed by k) from i to j using xkij . Following our convention, this should be written xkij . Authors need to strike a balance between a standard notational style and existing conventions. 2 Modeling time A survey of the literature reveals different styles toward modeling time.
The problem arises because the proper convention for modeling time for information processes is different than what should be used for physical processes. We begin by establishing the relationship between discrete and continuous time. All of the models in this book are presented in discrete time, since this is the most natural framework for computation. 1. When we are modeling information, time t = 0 is special; it represents “here and now” with the information that is available at the moment. 1a).
We can also have shortest path problems defined over infinite horizons, although we would typically include a discount factor. We are often interested in problems where there is some source of uncertainty. For our shortest path problem, it is natural to view the cost on a link as random, reflecting the variability in the travel time over each link. There are two ways we can handle the uncertainty. The simplest is to assume that our driver has to make a decision before seeing the travel time over the link.