Research Output

Understanding environmental influence in an open-ended evolutionary algorithm.

  It is well known that in open-ended evolution, the nature
of the environment plays in key role in directing evolution. However, in Evolutionary Robotics, it is often unclear exactly how parameterisation of a given environment might influence the emergence of particular behaviours. We consider environments in which the total amount of energy
is parameterised by availability and value, and use surface plots to explore the relationship between those environment parameters and emergent behaviour using a variant of a well-known distributed evolutionary algorithm (mEDEA). Analysis of the resulting landscape show that it is crucial for a researcher to select appropriate parameterisations in order that the environment provides the right balance between facilitating survival and exerting sufficient pressure for new behaviours to emerge.
To the best of our knowledge, this is the fi rst time such an analysis has been undertaken.

  • Date:

    31 August 2016

  • Publication Status:

    Published

  • Publisher

    Springer

  • DOI:

    10.1007/978-3-319-45823-6_86

  • Library of Congress:

    QA75 Electronic computers. Computer science

  • Dewey Decimal Classification:

    004.2 Systems analysis, design & performance

Citation

Steyven, A., Hart, E. & Paechter, B. (2016). Understanding environmental influence in an open-ended evolutionary algorithm. In Parallel Problem Solving from Nature – PPSN XIV, 921-931. doi:10.1007/978-3-319-45823-6_86. ISBN 978-3-319-45822-9

Authors

Keywords

Evolutionary algorithm; evolutionary robotics; energy zones;

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