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From Shortest Paths to Reinforcement Learning

A MATLAB-Based Tutorial on Dynamic Programming

  • Textbook
  • © 2021

Overview

Authors:
  1. Paolo Brandimarte

    1. DISMA, Politecnico di Torino, Torino, Italy

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  • Covers both, classical numerical analysis approaches and more recent learning strategies based on Monte Carlo simulation
  • Includes well-documented MATLAB code snapshots to illustrate algorithms and applications in detail
  • Illustrate subtle modeling issues in detail
  • Illustrates a wide set of applications
  • Includes supplementary material: sn.pub/extras

Part of the book series: EURO Advanced Tutorials on Operational Research (EUROATOR)

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Table of contents (7 chapters)

  1. Front Matter

    Pages i-xi
    Download chapter PDF

  2. The Dynamic Programming Principle

    • Paolo Brandimarte
    Pages 1-34

  3. Implementing Dynamic Programming

    • Paolo Brandimarte
    Pages 35-66

  4. Modeling for Dynamic Programming

    • Paolo Brandimarte
    Pages 67-97

  5. Numerical Dynamic Programming for Discrete States

    • Paolo Brandimarte
    Pages 99-140

  6. Approximate Dynamic Programming and Reinforcement Learning for Discrete States

    • Paolo Brandimarte
    Pages 141-160

  7. Numerical Dynamic Programming for Continuous States

    • Paolo Brandimarte
    Pages 161-183

  8. Approximate Dynamic Programming and Reinforcement Learning for Continuous States

    • Paolo Brandimarte
    Pages 185-204

  9. Back Matter

    Pages 205-207
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Keywords

About this book

Dynamic programming (DP) has a relevant history as a powerful and flexible optimization principle, but has a bad reputation as a computationally impractical tool. This book fills a gap between the statement of DP principles and their actual software implementation. Using MATLAB throughout, this tutorial gently gets the reader acquainted with DP and its potential applications, offering the possibility of actual experimentation and hands-on experience. The book assumes basic familiarity with probability and optimization, and is suitable to both practitioners and graduate students in engineering, applied mathematics, management, finance and economics.

Authors and Affiliations

  • DISMA, Politecnico di Torino, Torino, Italy

    Paolo Brandimarte

About the author

Paolo Brandimarte is full professor at the Department of Mathematical Sciences of Politecnico di Torino, Italy, where he teaches courses on Business Analytics, Risk Management, and Operations Research. He is the author of more than ten books on the application of optimization and simulation methods to problems ranging from quantitative finance to production and supply chain management.

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