Stochastic Recursive Algorithms for Optimization Simultaneous Perturbation Methods /
Stochastic Recursive Algorithms for Optimization presents algorithms for constrained and unconstrained optimization and for reinforcement learning. Efficient perturbation approaches form a thread unifying all the algorithms considered. Simultaneous perturbation stochastic approximation and smooth fr...
| Κύριοι συγγραφείς: | , , |
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| Συγγραφή απο Οργανισμό/Αρχή: | |
| Μορφή: | Ηλεκτρονική πηγή Ηλ. βιβλίο |
| Γλώσσα: | English |
| Έκδοση: |
London :
Springer London : Imprint: Springer,
2013.
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| Σειρά: | Lecture Notes in Control and Information Sciences,
434 |
| Θέματα: | |
| Διαθέσιμο Online: | Full Text via HEAL-Link |
Πίνακας περιεχομένων:
- Part I: Introduction to Stochastic Recursive Algorithms
- Introduction
- Deterministic Algorithms for Local Search
- Stochastic Approximation Algorithms
- Part II: Gradient Estimation Schemes
- Kiefer-Wolfowitz Algorithm
- Gradient Schemes with Simultaneous Perturbation Stochastic Approximation
- Smoothed Functional Gradient Schemes
- Part III: Hessian Estimation Schemes
- Hessian Estimation with Simultaneous Perturbation Stochasti Approximation
- Smoothed Functional Hessian Schemes
- Part IV: Variations to the Basic Scheme
- Discrete Optimization
- Algorithms for Contrained Optimization
- Reinforcement Learning
- Part V: Applications
- Service Systems
- Road Traffic Control
- Communication Networks.
