Evolutionary Algorithms for Dynamic Environments: Prediction Using Linear Regression and Markov Chains

Authors:
Anabela Simões;Ernesto Costa
Affiliations:
Department of Informatics and Systems Engineering, Coimbra Polytechnic, and Centre of Informatics and Systems of the University of Coimbra,;Centre of Informatics and Systems of the University of Coimbra,
Venue:
Proceedings of the 10th international conference on Parallel Problem Solving from Nature: PPSN X
Year:
2008

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Abstract

In this work we investigate the use of prediction mechanisms in Evolutionary Algorithms for dynamic environments. These mechanisms, linear regression and Markov chains, are used to estimate the generation when a change in the environment will occur, and also to predict to which state (or states) the environment may change, respectively. Different types of environmental changes were studied. A memory-based evolutionary algorithm empowered by these two techniques was successfully applied to several instances of the dynamic bit matching problem.