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Fundamentals of Evolutionary Machine Learning

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Handbook of Evolutionary Machine Learning

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Abstract

In this opening chapter, we overview the quickly developing field of evolutionary machine learning. We first motivate the field and define how we understand evolutionary machine learning. Then we take a look at its roots, finding that it has quite a long history, going back to the 1950s. We introduce a taxonomy of the field, discuss the major branches of evolutionary machine learning, and conclude by outlining open problems.

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Acknowledgements

This work is funded by the FCT–Foundation for Science and Technology, I.P./MCTES through national funds (PIDDAC), within the scope of CISUC R &D Unit–UIDB/00326/2020 or project code UIDP/00326/2020.

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  1. Department of Computer Science and Engineering, Michigan State University, East Lansing, MI, 48864, USA

    Wolfgang Banzhaf

  2. Department of Informatics Engineering, Centre for Informatics and Systems of the University of Coimbra, University of Coimbra, 3004-531, Coimbra, Portugal

    Penousal Machado

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  1. Department of Computer Science and Engineering, Michigan State University, East Lansing, MI, USA

    Wolfgang Banzhaf

  2. Department of Informatics Engineering, University of Coimbra, Coimbra, Portugal

    Penousal Machado

  3. School of Engineering and Computer Science and Centre for Data Science and Artificial Intelligence, Victoria University of Wellington, Wellington, New Zealand

    Mengjie Zhang

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Banzhaf, W., Machado, P. (2024). Fundamentals of Evolutionary Machine Learning. In: Banzhaf, W., Machado, P., Zhang, M. (eds) Handbook of Evolutionary Machine Learning. Genetic and Evolutionary Computation. Springer, Singapore. https://doi.org/10.1007/978-981-99-3814-8_1

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