Introduction to statistical models for populational optimization
This paper provides an introductory review of populational search
methods based on statistical modelling. We start with a random search
algorithm called Markov Chain Monte Carlo (MCMC).
To solve an optimization problem,
it is crucial for the performance to use specific knowledge about the problem.
We discuss how the optimizer
can acquire the knowledge during the optimization,
which is closely related to various fields of
statistical learning theory.