Guiding the Exploration of the Solution Space in Walking Robots Through Growth-Based Morphological Development

Martin Naya, Andres Faina, Richard Duro

Research output: Conference Article in Proceeding or Book/Report chapterArticle in proceedingsResearchpeer-review


In human beings, the joint development of the body and cognitive system has been shown to facilitate the acquisition of new skills and abilities. In the literature, these natural principles have been applied to robotics with mixed results and different authors have suggested several hypotheses to explain them. One of the most popular hypotheses states that morphological development improves learning by increasing exploration of the solution space, avoiding stagnation in local optima. In this article, we are going to study the influence of growth-based morphological development and its nuances as a tool to improve the exploration of the solution space. We will perform a series of experiments over two different robot morphologies which learn to walk. Furthermore, we will compare these results to another optimization strategy that has been shown to be useful to favor exploration in learning algorithms: the application of noise during learning. Finally, to check if the increased exploration hypothesis holds, we visualize the genotypic space during learning considering the different optimization strategies by using the Search Trajectory Network representation. The results indicate that noise and growth increase exploration, but only growth guides the search towards good solutions.
Original languageEnglish
Title of host publicationGECCO '23: Proceedings of the Genetic and Evolutionary Computation Conference
PublisherAssociation for Computing Machinery
Publication date2023
Publication statusPublished - 2023
EventGECCO '23: Genetic and Evolutionary Computation Conference - Lisbon , Portugal
Duration: 15 Jul 202319 Jul 2023


ConferenceGECCO '23: Genetic and Evolutionary Computation Conference


  • Cognitive Development
  • Robotics
  • Morphological Development
  • Optimization Strategies
  • Exploration in Learning


Dive into the research topics of 'Guiding the Exploration of the Solution Space in Walking Robots Through Growth-Based Morphological Development'. Together they form a unique fingerprint.

Cite this