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1.

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図書
1. Introduction to stochastic dynamic programming (: pbk)
Sheldon Ross
出版情報: Orlando ; Tokyo : Academic Press, c1983  xi, 164 p. ; 24 cm
シリーズ名: Probability and mathematical statistics : a series of monographs and textbooks
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目次情報: 続きを見る
Preface
Finite-Stage Models / I.：
Introduction / 1.：
A Gambling Model / 2.：
A Stock-Option Model / 3.：
Modular Functions and Monotone Policies / 4.：
Accepting the Best Offer / 5.：
A Sequential Allocation Model / 6.：
The Interchange Argument in Sequencing / 7.：
Problems
Notes and References
Discounted Dynamic Programming / II.：
The Optimality Equation and Optimal Policy
Method of Successive Approximations
Policy Improvement
Solution by Linear Programming
Extension to Unbounded Rewards
References
Minimizing Costs--Negative Dynamic Programming / III.：
Introduction and Some Theoretical Results
Optimal Stopping Problems
Bayesian Sequential Analysis
Computational Approaches
Optimal Search
Maximizing Rewards--Positive Dynamic Programming / IV.：
Introduction and Main Theoretical Results
Applications to Gambling Theory
Computational Approaches to Obtaining V
Average Reward Criterion / V.：
Introduction and Counterexamples
Existence of an Optimal Stationary Policy
Stochastic Scheduling / VI.：
Maximizing Finite-Time Returns--Single Processor
Minimizing Expected Makespan--Processors in Parallel
Minimizing Expected Makespan--Processors in Series
Maximizing Total Field Life
A Stochastic Knapsack Model
A Sequential-Assignment Problem
Bandit Processes / VII.：
Single-Project Bandit Processes
Multiproject Bandit Processes
An Extension and a Nonextension
Generalizations of the Classical Bandit Problem
Stochastic Order Relations / Appendix：
Stochastically Larger
Coupling
Hazard-Rate Ordering
Likelihood-Ratio Ordering
Reference
Index
Preface
Finite-Stage Models / I.：
Introduction / 1.：
2.

図書
図書
2. Dynamic programming and partial differential equations
Edward Angel, Richard Bellman
出版情報: New York : Academic Press, 1972  xi, 204 p. ; 24 cm
シリーズ名: Mathematics in science and engineering : a series of monographs and textbooks ; v. 88
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3.

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3. The optimal design of chemical reactors : a study in dynamic programming
Rutherford Aris
出版情報: New York : Academic Press, 1961  xi, 191 p. ; 24 cm
シリーズ名: Mathematics in science and engineering : a series of monographs and textbooks ; v. 3
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4. Algorithms, graphs, and computers
Richard Bellman, Kenneth L. Cooke, Jo Ann Lockett
出版情報: New York : Academic Press, 1970  xv, 246 p. ; 24 cm
シリーズ名: Mathematics in science and engineering : a series of monographs and textbooks ; v. 62
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5.

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図書
5. Nonserial dynamic programming
[by] Umberto Bertelè and Francesco Brioschi
出版情報: New York : Academic Press, 1972  xii, 235 p. ; 24 cm
シリーズ名: Mathematics in science and engineering : a series of monographs and textbooks ; v. 91
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6.

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6. Dynamic programming and its application to optimal control
[by] R. Boudarel, J. Delmas [and] P. Guichet ; translated by R.N. McDonough
出版情報: New York : Academic Press, 1971  xiv, 252 p. ; 24 cm
シリーズ名: Mathematics in science and engineering : a series of monographs and textbooks ; v. 81
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7.

図書
図書
7. The art and theory of dynamic programming
Stuart E. Dreyfus, Averill M. Law
出版情報: New York ; San Diego ; Tokyo : Academic Press, 1977  xv, 284 p. ; 24 cm
シリーズ名: Mathematics in science and engineering : a series of monographs and textbooks ; v. 130
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8.

図書
図書
8. Dynamic programming and stochastic control
Dimitri P. Bertsekas
出版情報: New York : Academic Press, 1976  xv, 397 p. ; 24 cm
シリーズ名: Mathematics in science and engineering : a series of monographs and textbooks ; v. 125
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9.

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9. Spatial development planning : a dynamic convex programming approach
Masahisa Fujita
出版情報: Amsterdam : North-Holland Pub. Co. , New York : distributors for the U.S. and Canada, Elsevier North-Holland, 1978  xvi, 335 p. ; 25 cm
シリーズ名: Studies in regional science and urban economics ; v. 2
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10.

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図書
10. Dynamic programming and Markov processes
Ronald A. Howard
出版情報: Cambridge, Mass. : M.I.T. Press, c1960  viii, 136 p. ; 24 cm
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11. Dynamic programming and Markov potential theory. 2nd ed.
A. Hordijk
出版情報: Amsterdam : Mathematisch Centrum, 1977  viii, 134 p. ; 24 cm
シリーズ名: Mathematical Centre tracts ; 51
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12.

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12. Dynamic programming
by Richard Bellman
出版情報: Princeton : Princeton University Press, 1957  xxv, 339 p. ; 24 cm
シリーズ名: Rand Corporation research study
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13.

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図書
13. Dynamic programming
Moshe Sniedovich
出版情報: New York, N.Y. : M. Dekker, c1992  viii, 410 p. ; 24 cm
シリーズ名: Monographs and textbooks in pure and applied mathematics ; 154
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14.

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14. Nonlinear and dynamic programming
by G. Hadley
出版情報: Reading, Mass. : Addison-Wesley Pub., 1964  xi, 484 p. ; 24 cm
シリーズ名: Addison-Wesley series in management science and economics
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15.

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15. Finite dynamic programming : an approach to finite Markov decision processes
D.J. White
出版情報: Chichester [Eng.] ; New York : Wiley, c1978  xiii, 204 p. ; 24 cm
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16.

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16. Nonlinear and dynamic programming
by G. Hadley
出版情報: Reading, Mass. : Addison-Wesley Pub. Co, [1970], c1964  xi, 484 p. ; 22 cm
シリーズ名: Addison-Wesley world student series
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17.

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図書
17. Discrete dynamic programming : an introduction to the optimization of staged processes. 1st ed
Rutherford Aris
出版情報: New York : Blaisdell, 1964  x, 148 p. ; 23 cm
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18.

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18. Nonlinear and dynamic programming ; an introduction (: us ; : au)
Sven Danø
出版情報: New York ; Wien : Springer-Verlag, 1975  164 p. ; 24 cm
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19.

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19. Basic analytic and computational methods
Larson, Robert Edward ; Casti, John L., 1943-
出版情報: New York : M. Dekker, c1978  xi, 330 p. ; 24 cm
シリーズ名: Control and systems theory / editor, Jerry M. Mendel ; associate editors, Karl J. Aström, Michael Athans, David G. Luenberger ; v. 7 . Principles of dynamic programming / by Robert E. Larson and John L. Casti ; pt. 1
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20.

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20. Advanced theory and applications
Larson, Robert Edward ; Casti, John L., 1943-
出版情報: New York : M. Dekker, c1982  497 p. ; 24 cm
シリーズ名: Control and systems theory / editor, Jerry M. Mendel ; associate editors, Karl J. Aström, Michael Athans, David G. Luenberger ; v.7 . Principles of dynamic programming / by Robert E. Larson, John L. Casti ; pt. 2
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21.

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21. Differential dynamic programming
[by] David H. Jacobson [and] David Q. Mayne
出版情報: New York : American Elsevier Pub. Co., 1970  208 p. ; 24 cm
シリーズ名: Modern analytic and computational methods in science and mathematics ; v. 24
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22.

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22. Dynamic programming and the calculus of variations
Stuart E. Dreyfus
出版情報: New York : Academic Press, 1965  xix, 248 p. ; 24 cm
シリーズ名: Mathematics in science and engineering : a series of monographs and textbooks ; v. 21
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23. Finite state Markovian decision processes
Cyrus Derman
出版情報: New York ; Tokyo : Academic Press, 1970  xiii, 159 p ; 24 cm
シリーズ名: Mathematics in science and engineering : a series of monographs and textbooks ; v. 67
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24.

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24. Decision and control in uncertain resource systems
Marc Mangel
出版情報: Orlando : Academic Press, c1985  xiii, 255 p. ; 24 cm
シリーズ名: Mathematics in science and engineering : a series of monographs and textbooks ; v. 172
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25.

図書
図書
25. Approximate dynamic programming : solving the curses of dimensionality. 2nd ed (: hard)
Warren B. Powell
出版情報: Hoboken, N.J. : Wiley, c2011  xviii, 627 p. ; 25 cm
シリーズ名: Wiley series in probability and mathematical statistics
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目次情報: 続きを見る
Preface to the Second Edition
Preface to the First Edition
Acknowledgments
The Challenges of Dynamic Programming / 1：
A Dynamic Programming Example: A Shortest Path Problem / 1.1：
The Three Curses of Dimensionality / 1.2：
Some Real Applications / 1.3：
Problem Classes / 1.4：
The Many Dialects of Dynamic Programming / 1.5：
What Is New in This Book? / 1.6：
Pedagogy / 1.7：
Bibliographic Notes / 1.8：
Some Illustrative Models / 2：
Deterministic Problems / 2.1：
Stochastic Problems / 2.2：
Information Acquisition Problems / 2.3：
A Simple Modeling Framework for Dynamic Programs / 2.4：
Problems / 2.5：
Introduction to Markov Decision Processes / 3：
The Optimality Equations / 3.1：
Finite Horizon Problems / 3.2：
Infinite Horizon Problems / 3.3：
Value Iteration / 3.4：
Policy Iteration / 3.5：
Hybrid Value-Policy Iteration / 3.6：
Average Reward Dynamic Programming / 3.7：
The Linear Programming Method for Dynamic Programs / 3.8：
Monotone Policies* / 3.9：
Why Does It Work?** / 3.10：
Introduction to Approximate Dynamic Programming / 3.11：
The Three Curses of Dimensionality (Revisited) / 4.1：
The Basic Idea / 4.2：
Q-Learning and SARSA / 4.3：
Real-Time Dynamic Programming / 4.4：
Approximate Value Iteration / 4.5：
The Post-Decision State Variable / 4.6：
Low-Dimensional Representations of Value Functions / 4.7：
So Just What Is Approximate Dynamic Programming? / 4.8：
Experimental Issues / 4.9：
But Does It Work? / 4.10：
Modeling Dynamic Programs / 4.11：
Notational Style / 5.1：
Modeling Time / 5.2：
Modeling Resources / 5.3：
The States of Our System / 5.4：
Modeling Decisions / 5.5：
The Exogenous Information Process / 5.6：
The Transition Function / 5.7：
The Objective Function / 5.8：
A Measure-Theoretic View of Information** / 5.9：
Policies / 5.10：
Myopic Policies / 6.1：
Lookahead Policies / 6.2：
Policy Function Approximations / 6.3：
Value Function Approximations / 6.4：
Hybrid Strategies / 6.5：
Randomized Policies / 6.6：
How to Choose a Policy? / 6.7：
Policy Search / 6.8：
Background / 7.1：
Gradient Search / 7.2：
Direct Policy Search for Finite Alternatives / 7.3：
The Knowledge Gradient Algorithm for Discrete Alternatives / 7.4：
Simulation Optimization / 7.5：
Approximating Value Functions / 7.6：
Lookup Tables and Aggregation / 8.1：
Parametric Models / 8.2：
Regression Variations / 8.3：
Nonparametric Models / 8.4：
Approximations and the Curse of Dimensionality / 8.5：
Learning Value Function Approximations / 8.6：
Sampling the Value of a Policy / 9.1：
Stochastic Approximation Methods / 9.2：
Recursive Least Squares for Linear Models / 9.3：
Temporal Difference Learning with a Linear Model / 9.4：
Bellman's Equation Using a Linear Model / 9.5：
Analysis of TD(0), LSTD, and LSPE Using a Single State / 9.6：
Gradient-Based Methods for Approximate Value Iteration* / 9.7：
Least Squares Temporal Differencing with Kernel Regression* / 9.8：
Value Function Approximations Based on Bayesian Learning* / 9.9：
Why Does It Work* / 9.10：
Optimizing While Learning / 9.11：
Overview of Algorithmic Strategies / 10.1：
Approximate Value Iteration and Q-Learning Using Lookup Tables / 10.2：
Statistical Bias in the Max Operator / 10.3：
Approximate Value Iteration and Q-Learning Using Linear Models / 10.4：
Approximate Policy Iteration / 10.5：
The Actor-Critic Paradigm / 10.6：
Policy Gradient Methods / 10.7：
The Linear Programming Method Using Basis Functions / 10.8：
Approximate Policy Iteration Using Kernel Regression* / 10.9：
Finite Horizon Approximations for Steady-State Applications / 10.10：
Adaptive Estimation and Stepsizes / 10.11：
Learning Algorithms and Stepsizes / 11.1：
Deterministic Stepsize Recipes / 11.2：
Stochastic Stepsizes / 11.3：
Optimal Stepsizes for Nonstationary Time Series / 11.4：
Optimal Stepsizes for Approximate Value Iteration / 11.5：
Convergence / 11.6：
Guidelines for Choosing Stepsize Formulas / 11.7：
Exploration Versus Exploitation / 11.8：
A Learning Exercise: The Nomadic Trucker / 12.1：
An Introduction to Learning / 12.2：
Heuristic Learning Policies / 12.3：
Gittins Indexes for Online Learning / 12.4：
The Knowledge Gradient Policy / 12.5：
Learning with a Physical State / 12.6：
Value Function Approximations for Resource Allocation Problems / 12.7：
Value Functions versus Gradients / 13.1：
Linear Approximations / 13.2：
Piecewise-Linear Approximations / 13.3：
Solving a Resource Allocation Problem Using Piecewise-Linear Functions / 13.4：
The SHAPE Algorithm / 13.5：
Regression Methods / 13.6：
Cutting Planes* / 13.7：
Dynamic Resource Allocation Problems / 13.8：
An Asset Acquisition Problem / 14.1：
The Blood Management Problem / 14.2：
A Portfolio Optimization Problem / 14.3：
A General Resource Allocation Problem / 14.4：
A Fleet Management Problem / 14.5：
A Driver Management Problem / 14.6：
Implementation Challenges / 14.7：
Will ADP Work for Your Problem? / 15.1：
Designing an ADP Algorithm for Complex Problems / 15.2：
Debugging an ADP Algorithm / 15.3：
Practical Issues / 15.4：
Modeling Your Problem / 15.5：
Online versus Offline Models / 15.6：
If It Works, Patent It! / 15.7：
Bibliography
Index
Preface to the Second Edition
Preface to the First Edition
Acknowledgments
26.

図書
図書
26. Dynamic programming
D. J. White
出版情報: Edinburgh : Oliver & Boyd , San Francisco : Holden-Day, 1969  vii, 180 p. ; 24 cm
シリーズ名: Mathematical economics texts ; 1
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27.

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27. Dynamic programming of economic decisions
Martin J. Beckmann
出版情報: Berlin ; New York [etc.] : Springer-Verlag, 1968  xii, 143 p. ; 24 cm
シリーズ名: Ökonometrie und Unternehmensforschung = Econometrics and operations research ; 9
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28. Mathematics of adaptive control processes
by Sidney J. Yakowitz
出版情報: New York : American Elsevier Pub. Co., 1969  xv, 158 p ; 24 cm
シリーズ名: Modern analytic and computational methods in science and mathematics ; v. 14
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29. Stochastic optimal control : the discrete time case
Dimitri P. Bertsekas, Steven E. Shreve
出版情報: New York : Academic Press, 1978  xiii, 323 p. ; 24 cm
シリーズ名: Mathematics in science and engineering : a series of monographs and textbooks ; v. 139
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30. Markov decision processes : discrete stochastic dynamic programming
Martin L. Puterman
出版情報: New York ; Chichester : Wiley, c1994  xvii, 649 p. ; 24 cm
シリーズ名: Wiley series in probability and mathematical statistics ; . Applied probability and statistics
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31.

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31. Applied optimal control : optimization, estimation, and control. Rev. printing (: pbk)
Arthur E. Bryson, Jr., Yu-Chi Ho
出版情報: Washington : Hemisphere Pub. Corp. , New York : distributed by Halsted Press, [1975]  481 p. ; 24 cm
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32.

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32. Introduction to dynamic programming
[by] George L. Nemhauser
出版情報: New York : Wiley, [1966]  xiii, 256 p ; 24 cm
シリーズ名: Series in decision and control
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33.

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33. Applied optimal control : optimization, estimation, and control
Arthur E. Bryson, Jr., Yu-Chi Ho
出版情報: Waltham, Mass. : Blaisdell Pub. Co, c1969  481 p. ; 24 cm
シリーズ名: A Blaisdell book in the pure and applied sciences
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34.

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34. Dynamic programming : sequential scientific management
A. Kaufmann, R. Cruon ; translated by Henry C. Sneyd
出版情報: New York : Academic Press, 1967  xv, 278 p. ; 24 cm
シリーズ名: Mathematics in science and engineering : a series of monographs and textbooks ; v. 37
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35.

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35. Dynamic programming and optimal control. 4th ed (v. 1)
Dimitri P. Bertsekas
出版情報: Belmont, Mass. : Athena Scientific, c2017  xix, 555 p. ; 24 cm
シリーズ名: Athena Scientific optimization and computation series
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