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Evolutionary Algorithms and Hyper-Heuristics

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Automatic Design of Decision-Tree Induction Algorithms

Part of the book series: SpringerBriefs in Computer Science ((BRIEFSCOMPUTER))

Abstract

This chapter presents the basic concepts of evolutionary algorithms (EAs) and hyper-heuristics (HHs), which are computational techniques directly explored in this book. EAs are well-known population-based metaheuristics. They have been employed in artificial intelligence over several years with the goal of providing the near-optimal solution for a problem that comprises a very large search space. A general overview of EAs is presented in Sect. 3.1. HHs, in turn, are a recently new field in the optimisation research area, in which a metaheuristic—often an EA, and this is why these related concepts are reviewed together in this chapter—is used for searching in the space of heuristics (algorithms), and not in the space of solutions, like conventional metaheuristics. The near-optimal heuristic (algorithm) provided by a HHs approach can be further employed in several distinct problems, instead of relying on a new search process for each new problem to be solved. An overview of HHs is given in Sect. 3.2.

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Notes

  1. 1.

    For instance, Angeline [1] argues that the lack of performance of standard GP crossover (in comparison to some types of macromutations) indicates that it is, in effect, more accurately described as a population-limited macromutation operation rather than an operation consistent with the building block hypothesis.

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Authors and Affiliations

  1. Faculdade de Informática, Pontifícia Universidade Católica do Rio Grande do Sul, Porto Alegre, RS, Brazil

    Rodrigo C. Barros

  2. Instituto de Ciências Matemáticas e de Computação, Universidade de São Paulo, São Carlos, SP, Brazil

    André C. P. L. F. de Carvalho

  3. School of Computing, University of Kent, Canterbury, Kent, UK

    Alex A. Freitas

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  1. Rodrigo C. Barros
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  2. André C. P. L. F. de Carvalho
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  3. Alex A. Freitas
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Correspondence to Rodrigo C. Barros .

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Barros, R.C., de Carvalho, A.C.P.L.F., Freitas, A.A. (2015). Evolutionary Algorithms and Hyper-Heuristics. In: Automatic Design of Decision-Tree Induction Algorithms. SpringerBriefs in Computer Science. Springer, Cham. https://doi.org/10.1007/978-3-319-14231-9_3

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  • DOI: https://doi.org/10.1007/978-3-319-14231-9_3

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