Studying the evolvability of self-encoding genotype-phenotype maps

Andrew M. Webb*, Joshua Knowles

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We introduce a model of reproduction in which the genotypephenotype (G-P) map is able to evolve. In this model, Each organism implements a G-P map, determining how the organism is encoded in its genome. Crucially, it also determines how the G-P map itself is encoded. We call these maps 'self-encoding'. We relate this model to recent artificial life research, and back to the seminal work of John von Neumann. We simulate populations of organisms that have as their genome and G-P map the axiom and production rules of an L-system. The populations are given the task of optimizing a dynamic fitness function. Our purpose is to study whether the self-encoding property has any effect on the evolution of evolvability, and to look for other factors that lead to the evolution of G-P maps that confer evolvability. We find that evolvability does evolve, but only when we add constraints to the model.

Original languageEnglish
Title of host publicationArtificial Life 14 - Proceedings of the 14th International Conference on the Synthesis and Simulation of Living Systems, ALIFE 2014
EditorsHiroki Sayama, John Rieffel, Sebastian Risi, Rene Doursat, Hod Lipson
PublisherMIT Press Journals
Pages79-86
Number of pages8
ISBN (Electronic)9780262326216
Publication statusPublished - 2014
Event14th International Conference on the Synthesis and Simulation of Living Systems, ALIFE 2014 - Manhattan, United States
Duration: 30 Jul 20142 Aug 2014

Publication series

NameArtificial Life 14 - Proceedings of the 14th International Conference on the Synthesis and Simulation of Living Systems, ALIFE 2014

Conference

Conference14th International Conference on the Synthesis and Simulation of Living Systems, ALIFE 2014
Country/TerritoryUnited States
CityManhattan
Period30/07/142/08/14

Bibliographical note

Publisher Copyright:
© Artificial Life 14 - Proceedings of the 14th International Conference on the Synthesis and Simulation of Living Systems, ALIFE 2014. All rights reserved.

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Artificial Intelligence
  • Modelling and Simulation

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