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OMNIREP: originating meaning by coevolving encodings and representations

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Abstract

A major effort in the practice of evolutionary computation goes into deciding how to represent individuals in the evolving population. This task is actually composed of two subtasks: defining a data structure that is the representation and defining the encoding that enables to interpret the representation. In this paper we employ a coevolutionary algorithm—dubbed OMNIREP—to discover both a representation and an encoding that solve a particular problem of interest. We describe four experiments that provide a proof-of-concept of OMNIREP’s essential merit. We think that the proposed methodology holds potential as a problem solver and also as an exploratory medium when scouting for good representations.

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Notes

  1. www.johndcook.com/blog/2009/04/06/anatomy-of-a-floating-point-number.

  2. The OMNIREP code is available at https://github.com/EpistasisLab/.

  3. Some parameters may seem arbitrary but our recent findings provide some justification for this [25].

  4. www.rogerjohansson.blog/2008/12/07/genetic-programming-evolution-of-mona-lisa/.

  5. Of course, some representations, such as trees in genetic programming, are inherently variable-length. Herein, we simply refer to the literature on “variable-length genomes”.

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Acknowledgements

This work was supported by National Institutes of Health grants AI116794, DK112217, ES013508, HL134015, LM010098, LM011360, LM012601, and TR001263.

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Authors and Affiliations

  1. Institute for Biomedical Informatics (IBI), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA

    Moshe Sipper & Jason H. Moore

  2. Department of Computer Science, Ben-Gurion University, 8410501, Beersheba, Israel

    Moshe Sipper

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  1. Moshe Sipper
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  2. Jason H. Moore
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Correspondence to Moshe Sipper.

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Sipper, M., Moore, J.H. OMNIREP: originating meaning by coevolving encodings and representations. Memetic Comp. 11, 251–261 (2019). https://doi.org/10.1007/s12293-019-00285-2

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