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Title: Regulatory mechanism predates the evolution of self-organizing capacity in simulated ant-like robots
Authors: Fujisawa, Ryusuke
Ichinose, Genki
Dobata, Shigeto  kyouindb  KAKEN_id
Author's alias: 藤澤, 隆介
一ノ瀬, 元喜
土畑, 重人
Keywords: Complexity
Evolutionary theory
Social evolution
Issue Date: 18-Jan-2019
Publisher: Springer Nature
Journal title: Communications Biology
Volume: 2
Thesis number: 25
Abstract: The evolution of complexity is one of the prime features of life on Earth. Although well accepted as the product of adaptation, the dynamics underlying the evolutionary build-up of complex adaptive systems remains poorly resolved. Using simulated robot swarms that exhibit ant-like group foraging with trail pheromones, we show that their self-organizing capacity paradoxically involves regulatory behavior that arises in advance. We focus on a traffic rule on their foraging trail as a regulatory trait. We allow the simulated robot swarms to evolve pheromone responsiveness and traffic rules simultaneously. In most cases, the traffic rule, initially arising as selectively neutral component behaviors, assists the group foraging system to bypass a fitness valley caused by overcrowding on the trail. Our study reveals a hitherto underappreciated role of regulatory mechanisms in the origin of complex adaptive systems, as well as highlights the importance of embodiment in the study of their evolution.
Description: 生物の複雑適応システムの進化機序に新たな規則を発見 --アリロボットの群れを「飼いならす」--. 京都大学プレスリリース. 2019-01-29.
Rights: © The Author(s) 2019. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
URI: http://hdl.handle.net/2433/236120
DOI(Published Version): 10.1038/s42003-018-0276-3
PubMed ID: 30675523
Related Link: http://www.kyoto-u.ac.jp/ja/research/research_results/2018/190118_1.html
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