@inbook{9ebd59eb357a401990cbcb972a4917bb,
title = "A survey of some model-based methods for global optimization",
abstract = "We review some recent developments of a class of random search methods: model-based methods for global optimization problems. Probability models are used to guide the construction of candidate solutions in model-based methods, which makes them easy to implement and applicable to problems with little structure. We have developed various frameworks for model-based algorithms to guide the updating of probabilistic models and to facilitate convergence proofs. Specific methods covered in this survey include model reference adaptive search, a particle-filtering approach, an evolutionary games approach, and a stochastic approximation-based gradient approach.",
keywords = "Candidate Solution, Evolutionary Game, Global Optimal Solution, Replicator Dynamic, Stochastic Approximation",
author = "Jiaqiao Hu and Yongqiang Wang and Enlu Zhou and Fu, \{Michael C.\} and Marcus, \{Steven I.\}",
note = "Publisher Copyright: {\textcopyright} 2012, Springer Science+Business Media, LLC.",
year = "2012",
doi = "10.1007/978-0-8176-8337-5\_10",
language = "English",
series = "Systems and Control: Foundations and Applications",
publisher = "Birkhauser",
number = "9780817683368",
pages = "157--179",
booktitle = "Systems and Control",
edition = "9780817683368",
}