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Dynamic Programming

Thomas J. Sargent · John Stachurski

These books offer a unified treatment of dynamic programming, from finite-state foundations to a complete reworking of the theory for general state spaces. Applications span economics, finance, and operations research.

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General States

9 chapters
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Forthcoming from Cambridge University Press, 2027 · How to cite

Overview Lectures

High-level introduction covering both volumes.

Lecture 1 (PDF) Lecture 2 (PDF)

Contents

Volume I — Finite States

  1. Introduction
  2. Operators and Fixed Points
  3. Markov Dynamics
  4. Optimal Stopping
  5. Markov Decision Processes
  6. Stochastic Discounting
  7. Valuation
  8. Recursive Decision Processes
  9. Abstract Dynamic Programming
  10. Continuous Time

Volume II — General States

  1. Prelude: Examples of Dynamic Programs
  2. Abstract Decision Processes
  3. ADPs on Pospace
  4. ADPs on Banach Space
  5. ADP Transformations
  6. Linear Decision Processes
  7. Recursive Decision Processes
  8. Additional Applications
  9. Approximation and Learning

How to cite

Please cite the Cambridge University Press editions, including when working from the free PDFs or online editions.

Volume I — Finite States

Sargent, Thomas J. and John Stachurski (2025). Dynamic Programming: Finite States. Cambridge University Press. https://doi.org/10.1017/9781009540780 

@book{sargent_stachurski_2025,
  author    = {Sargent, Thomas J. and Stachurski, John},
  title     = {Dynamic Programming: Finite States},
  publisher = {Cambridge University Press},
  address   = {Cambridge},
  year      = {2025},
  doi       = {10.1017/9781009540780}
}
Download .bib

Volume II — General States

Sargent, Thomas J. and John Stachurski (forthcoming, 2027). Dynamic Programming: General States. Cambridge University Press. 

@book{sargent_stachurski_2027,
  author    = {Sargent, Thomas J. and Stachurski, John},
  title     = {Dynamic Programming: General States},
  publisher = {Cambridge University Press},
  address   = {Cambridge},
  year      = {2027},
  note      = {Forthcoming},
  url       = {https://dp.quantecon.org/}
}
Download .bib

Both entries: dp.bib