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ORIGINAL RESEARCH article

Front. Robot. AI
Sec. Robot Learning and Evolution
Volume 11 - 2024 | doi: 10.3389/frobt.2024.1470886

Global Progress in Competitive Co-Evolution: a Systematic Comparison of Alternative Methods

Provisionally accepted
Stefano Nolfi Stefano Nolfi Paolo Pagliuca Paolo Pagliuca *
  • National Research Council (CNR), Roma, Italy

The final, formatted version of the article will be published soon.

    We investigate the use of competitive co-evolution for synthesizing progressively better solutions. Specifically, we introduce a set of methods to measure historical and global progress. We discuss the factors that facilitate genuine progress. Finally, we compare the efficacy of four qualitatively different algorithms, including two newly introduced methods. The selected algorithms promote genuine progress by creating an archive of opponents used to evaluate evolving individuals, generating archives that include high-performing and well-differentiated opponents, identifying and discarding variations that lead to local progress only (i.e. progress against the opponents experienced and retrogressing against others). The results obtained in a predator-prey scenario, commonly used to study competitive evolution, demonstrate that all the considered methods lead to global progress in the long term. However, the rate of progress and the ratio of progress versus retrogressions vary significantly among algorithms.

    Keywords: Competitive co-evolution, Evolutionary Robotics, local historical and global progress, Open-Ended Evolution, predator-prey robots

    Received: 26 Jul 2024; Accepted: 23 Dec 2024.

    Copyright: © 2024 Nolfi and Pagliuca. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Paolo Pagliuca, National Research Council (CNR), Roma, Italy

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.