Finite-Time Behavior of the Annealing Algorithm

  • R. H. J. M. Otten
  • L. P. P. P. van Ginneken
Part of the The Kluwer International Series in Engineering and Computer Science book series (SECS, volume 72)


In chapter 5 we derived that the probability that an annealing chain has s as its current state will go asymptotically to δ(s, t), the corresponding value of the equilibrium density. Nothing was said however about how fast these probabilities will approach the equilibrium density. Yet it is necessary to know a priori when the actual density is close enough to the equilibrium density to change the value of the control parameter and to start with another chain. In this chapter we want to address that problem.


Optimal Schedule Equilibrium Density Local Accessibility Schedule Length Iterative Improvement 
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

© Kluwer Academic Publishers 1989

Authors and Affiliations

  • R. H. J. M. Otten
    • 1
  • L. P. P. P. van Ginneken
    • 2
  1. 1.Delft University of TechnologyThe Netherlands
  2. 2.Eindhoven University of TechnologyThe Netherlands

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