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Applying Ecological Principles to Genetic Programming

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Book cover Genetic Programming Theory and Practice XV

Part of the book series: Genetic and Evolutionary Computation ((GEVO))

Abstract

In natural ecologies, niches are created, altered, or destroyed, driving populations to continually change and produce novel features. Here, we explore an approach to guiding evolution via the power of niches: ecologically-mediated hints. The original exploration of ecologically-mediated hints occurred in Eco-EA, an algorithm in which an experimenter provides a primary fitness function for a tough problem that they are trying to solve, as well as “hints” that are associated with limited resources. We hypothesize that other evolutionary algorithms that create niches, such as lexicase selection, can be provided hints in a similar way. Here, we use a toy problem to investigate the expected benefits of using this approach to solve more challenging problems. Of course, since humans are notoriously bad at choosing fitness functions, user-provided advice may be misleading. Thus, we also explore the impact of misleading hints. As expected, we find that informative hints facilitate solving the problem. However, the mechanism of niche-creation (Eco-EA vs. lexicase selection) dramatically impacts the algorithm’s robustness to misleading hints.

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Author information

Authors and Affiliations

  1. BEACON Center for the Study of Evolution in Action and Department of Computer Science and Ecology, Evolutionary Biology, and Behavior Program, Michigan State University, East Lansing, MI, USA

    Emily Dolson & Charles Ofria

  2. BEACON Center for the Study of Evolution in Action and Department of Computer Science, Michigan State University, East Lansing, MI, USA

    Wolfgang Banzhaf

Authors
  1. Emily Dolson
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  2. Wolfgang Banzhaf
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  3. Charles Ofria
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Corresponding author

Correspondence to Emily Dolson .

Editor information

Editors and Affiliations

  1. BEACON Center for the Study of Evolution in Action and Department of Computer Science, Michigan State University, East Lansing, Michigan, USA

    Wolfgang Banzhaf

  2. Institute for Biomedical Informatics, University of Pennsylvania, Philadelphia, Pennsylvania, USA

    Randal S. Olson

  3. Institute for Biomedical Informatics, University of Pennsylvania, Philadelphia, Pennsylvania, USA

    William Tozier

  4. Center for the Study of Complex Systems, University of Michigan, Ann Arbor, Michigan, USA

    Rick Riolo

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Dolson, E., Banzhaf, W., Ofria, C. (2018). Applying Ecological Principles to Genetic Programming. In: Banzhaf, W., Olson, R., Tozier, W., Riolo, R. (eds) Genetic Programming Theory and Practice XV. Genetic and Evolutionary Computation. Springer, Cham. https://doi.org/10.1007/978-3-319-90512-9_5

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  • DOI: https://doi.org/10.1007/978-3-319-90512-9_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-90511-2

  • Online ISBN: 978-3-319-90512-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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