From Shortest Paths to Reinforcement Learning
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From Shortest Paths to Reinforcement Learning by Paolo Brandimarte
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.
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.
| SKU | Unavailable |
| ISBN 13 | 9783030618667 |
| ISBN 10 | 3030618668 |
| Title | From Shortest Paths to Reinforcement Learning |
| Author | Paolo Brandimarte |
| Series | Euro Advanced Tutorials On Operational Research |
| Condition | Unavailable |
| Binding Type | Hardback |
| Publisher | Springer Nature Switzerland AG |
| Year published | 2021-01-12 |
| Number of pages | 207 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |