Actions for From Shortest Paths to Reinforcement Learning [electronic resource] : A MATLAB-Based Tutorial on Dynamic Programming

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From Shortest Paths to Reinforcement Learning [electronic resource] : A MATLAB-Based Tutorial on Dynamic Programming / by Paolo Brandimarte

Author
Brandimarte, Paolo
Published
Cham : Springer International Publishing : Imprint: Springer, 2021.
Edition
1st ed. 2021.
Physical Description
XI, 207 pages 67 illustrations : online resource
Additional Creators
SpringerLink (Online service)
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Series
Contents
The dynamic programming principle -- Implementing dynamic programming -- Modeling for dynamic programming -- Numerical dynamic programming for discrete states -- Approximate dynamic programming and reinforcement learning for discrete states -- Numerical dynamic programming for continuous states -- Approximate dynamic programming and reinforcement learning for continuous states.
Summary
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.
Subject(s)
ISBN
9783030618674
Digital File Characteristics
PDF
text file
Part Of
Springer Nature eBook
View MARC record | catkey: 32863342