Approximate Dynamic Programming and Reinforcement Learning for Discrete States-Reference-Cited by-同舟云学术

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Approximate Dynamic Programming and Reinforcement Learning for Discrete States

Published:2021 Issue: Volume: Page:141-160
ISSN:2364-687X
Container-title:EURO Advanced Tutorials on Operational Research
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Author:

Brandimarte Paolo

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-030-61867-4_5

Reference14 articles.

1. Bertsekas, D.P.: Dynamic Programming and Optimal Control, vol. 2, 4th edn. Athena Scientific, Belmont (2012)

2. Bertsekas, D.P.: Reinforcement Learning and Optimal Control. Athena Scientific, Belmont (2019)

3. Bertsekas, D.P., Tsitsiklis, J.N.: Neuro-Dynamic Programming. Athena Scientific, Belmont (1996)

4. Brandimarte, P.: Handbook in Monte Carlo Simulation: Applications in Financial Engineering, Risk Management, and Economics. Wiley, Hoboken (2014)

5. Brandimarte, P.: An Introduction to Financial Markets: A Quantitative Approach. Wiley, Hoboken (2018)

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