Friday, 15 November 2013

Call for Papers: Special Session for WCCI 2014 "Evolutionary Algorithms with Statistical & Machine Learning Techniques"

Introduction to the special session:

An evolutionary optimization algorithm can be viewed as a learning process - it learns properties of the problem in question and locates the optimal solution. Therefore, it is very natural to introduce statistical & machine learning (SML) techniques into evolutionary algorithms (EA). Some examples are the surrogate assist EAs and the EAs by building and sampling probability models, such as estimation of distribution algorithms (EDA), ant colony optimization (ACO), cross-entropy methods, covariance matrix adaptation evolution strategy (CMA-ES), etc. The combination of EAs and SML has been proven to be an efficient strategy for dealing with hard optimization problems. Not only the aforementioned approaches, but also other SML techniques, including regression, density estimation, classification, clustering, and other techniques, can be applied to guide the EA search. This special session aims at bringing researchers who are interested in this area together to review the current state-of-art, exchange the latest ideas and explore future directions.
The major topics of interest include, but are not limited to:
  • Theoretical work on EAs with SML
  • Experimental studies of EAs with SML
  • EAs with SML for multiobjective optimization problems
  • EAs with SML in dynamic environments
  • EAs with SML for expensive black-box optimization
  • Real-world/novel applications



The deadline for submissions to this special session is 20 December 2013.

Information for Authors:


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