Tutorial : Optimization via Simulation with Bayesian Statistics and Dynamic Programming

@inproceedings{Rose2012TutorialO,
  title={Tutorial : Optimization via Simulation with Bayesian Statistics and Dynamic Programming},
  author={Oliver Rose and Adelinde M. Uhrmacher},
  year={2012}
}
Bayesian statistics comprises a powerful set of methods for analyzing simulated systems. Combined with dynamic programming and other methods for sequential decision making under uncertainty, Bayesian methods have been used to design algorithms for finding the best of several simulated systems. When the dynamic program can be solved exactly, these algorithms have optimal average-case performance. In other situations, this dynamic programming analysis supports the development of approximate… CONTINUE READING