Learning and Optimization with Perturbation Analysis


As shown in Chapter 2, performance derivatives for Markov systems depend heavily on performance potentials. In this chapter, we first discuss the numerical methods and sample-path-based algorithms for estimating performance potentials, and we then derive the sample-path-based algorithms for estimating performance derivatives. In performance optimization, the process of estimating the potentials and performance derivatives from a sample path is called learning.


Markov Chain Service Time Sample Path Perturbation Analysis Stochastic Approximation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media, LLC 2007

Authors and Affiliations

  1. 1.Hong Kong University of Science and TechnologyKowloonHong Kong

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