1.

Record Nr.

UNINA9910484119403321

Autore

Brandimarte Paolo

Titolo

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

Pubbl/distr/stampa

Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021

ISBN

3-030-61867-6

Edizione

[1st ed. 2021.]

Descrizione fisica

1 online resource (XI, 207 p. 67 illus.)

Collana

EURO Advanced Tutorials on Operational Research, , 2364-6888

Disciplina

519.703

Soggetti

Operations research

Management science

Econometrics

Numerical analysis

Social sciences - Mathematics

Industrial Management

Operations Research and Decision Theory

Operations Research, Management Science

Quantitative Economics

Numerical Analysis

Mathematics in Business, Economics and Finance

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di contenuto

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.

Sommario/riassunto

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.