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Concluding Remarks

  • Abhijit Gosavi
Part of the Operations Research/Computer Science Interfaces Series book series (ORCS, volume 25)

Abstract

It is unfortunately true that even now there is a persistent belief that one cannot optimize a system when all one has is its simulation model. It will take some time for the science of simulation-based optimization to get the recognition it deserves in the field of stochastic optimization. One must not forget that simulation-based optimization is a reality today because some people decided to take “the path less traveled by” and made discoveries that changed its topography.

Keywords

Reinforcement Learning Stochastic Optimization Stochastic Dynamic Programming Learning Automaton Simulation Optimization 
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.

Copyright information

© Springer Science+Business Media New York 2003

Authors and Affiliations

  • Abhijit Gosavi
    • 1
  1. 1.Department of Industrial EngineeringThe State University of New YorkBuffaloUSA

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