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Item Details
| Title:
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SIMULATION-BASED OPTIMIZATION
PARAMETRIC OPTIMIZATION TECHNIQUES AND REINFORCEMENT LEARNING |
| By: |
Abhijit Gosavi |
| Format: |
Paperback |
| List price:
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£153.00 |
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We currently do not stock this item, please contact the publisher directly for
further information.
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| ISBN 10: |
144195354X |
| ISBN 13: |
9781441953544 |
| Publisher: |
SPRINGER-VERLAG NEW YORK INC. |
| Pub. date: |
3 December, 2010 |
| Edition: |
Softcover reprint of hardcover 1st ed. 2003 |
| Series: |
Operations Research/Computer Science Interfaces Series 25 |
| Pages: |
554 |
| Synopsis: |
Simulation-Based Optimization: Parametric Optimization Techniques and Reinforcement Learning introduces the evolving area of simulation-based optimization. The book's objective is two-fold: (1) It examines the mathematical governing principles of simulation-based optimization, thereby providing the reader with the ability to model relevant real-life problems using these techniques. (2) It outlines the computational technology underlying these methods. Taken together these two aspects demonstrate that the mathematical and computational methods discussed in this book do work. Broadly speaking, the book has two parts: (1) parametric (static) optimization and (2) control (dynamic) optimization. Some of the book's special features are: *An accessible introduction to reinforcement learning and parametric-optimization techniques. *A step-by-step description of several algorithms of simulation-based optimization. *A clear and simple introduction to the methodology of neural networks. *A gentle introduction to convergence analysis of some of the methods enumerated above. *Computer programs for many algorithms of simulation-based optimization. |
| Illustrations: |
XXVII, 554 p. |
| Publication: |
US |
| Imprint: |
Springer-Verlag New York Inc. |
| Returns: |
Returnable |
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