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Automatic Step Evolution

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Advances in Artificial Intelligence -- IBERAMIA 2014 (IBERAMIA 2014)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8864))

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Abstract

A common issue in Artificial Life research, and mainly in open-ended evolution simulations, is that of defining the bootstrap conditions of the simulations. One usual technique employed is the random initialization of individuals at the start of each simulation. However, by using this initialization method, we force the evolutionary process to always start from scratch, and thus require more time to accomplish the objective. Artificial Life simulations, being typically, very time consuming, suffer particularly when applying this method. In a previous paper we described a technique we call step evolution, analogous to incremental evolution techniques, that can be used to shorten the time needed to evolve complex behaviors in open-ended evolutionary simulations. In this paper we further extend this technique by automating the process of stepping the simulation. We provide results from experiments done on an open-ended evolution of foraging scenario, where agents evolve, adapting to a world with a day and night cycle. The results show that we can indeed automate this process and achieve a performance at least as good as on the best performant non-automated version.

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Author information

Authors and Affiliations

  1. CISUC, Department of Informatics Engineering, University of Coimbra, Coimbra, Portugal

    Tiago Baptista & Ernesto Costa

Authors
  1. Tiago Baptista
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  2. Ernesto Costa
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Correspondence to Tiago Baptista .

Editor information

Editors and Affiliations

  1. Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil

    Ana L.C. Bazzan

  2. Pontifica Universidad Católica (PUC), Santiago de Chile, Chile

    Karim Pichara

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Baptista, T., Costa, E. (2014). Automatic Step Evolution. In: Bazzan, A., Pichara, K. (eds) Advances in Artificial Intelligence -- IBERAMIA 2014. IBERAMIA 2014. Lecture Notes in Computer Science(), vol 8864. Springer, Cham. https://doi.org/10.1007/978-3-319-12027-0_32

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  • DOI: https://doi.org/10.1007/978-3-319-12027-0_32

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-12026-3

  • Online ISBN: 978-3-319-12027-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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