Heritability of morphological and behavioural traits in evolving robots

Matteo De Carlo, Eliseo Ferrante, Daan Zeeuwe, Jacintha Ellers, A. E. Eiben

Research output: Contribution to journalArticlepeer-review

Abstract

In the field of evolutionary robotics, choosing the correct genetic representation is a complicated and delicate matter, especially when robots evolve behaviour and morphology at the same time. One principal problem is the lack of methods or tools to investigate and compare representations. In this paper we introduce and evaluate such a tool based on the biological notion of heritability. Heritability captures the proportion of phenotypic variation caused by genotypic variation and is often used to better understand the transmissibility of traits in real biological systems. As a proof of concept, we compare the heritability of various robot traits in two systems, one using a direct (tree based) representation and one using an indirect (grammar based) representation. We measure changes in heritability during the course of evolution and investigate how direct and indirect representation can be biased towards more exploration or exploitation throughout the course of evolution. The empirical study shows that heritability can be a useful tool to analyze different representations without running complete evolutionary processes using them.

Original languageEnglish (US)
Pages (from-to)1733-1749
Number of pages17
JournalEvolutionary Intelligence
Volume17
Issue number3
DOIs
StatePublished - Jun 2024

Keywords

  • Evolutionary robotics
  • Heritability
  • Morphological evolution
  • Representation

ASJC Scopus subject areas

  • Mathematics (miscellaneous)
  • Computer Vision and Pattern Recognition
  • Cognitive Neuroscience
  • Artificial Intelligence

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