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Cited by 5Evolutionary Algorithms and ApplicationsEvolution and Genetic DynamicsModular Robots and Swarm Intelligence

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Evolution of Complex Niche-Constructing Behaviors and Ecological Inheritance of Adaptive Structures in a Physically Grounded Environment

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Chiba, Naoaki, Suzuki, Reiji, Arita, Takaya·2020·Frontiers in Robotics and AI
DOI 10.3389/frobt.2020.00045PMC PMC7805702
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Abstract

Niche construction is a process in which organisms modify the selection pressures on themselves and others through their ecological activities, and ecological inheritance is the consequence of niche construction inherited through generations. However, it is still unclear how such mutual interactions between robots or embodied agents and their physical environments can yield complex and divergent evolutionary processes or an open-ended evolution. Our purpose is to clarify what kind of complex and various niche-constructing behaviors evolve in a physically grounded environment under various conditions of ecological inheritance of constructed structures and spatial relationships. We focus on a predator-prey relationship, and constructed an evolutionary model in which a prey creature has to avoid predation through the construction of a structure composed of objects in a 2D physically simulated environment supported by a physics engine. We used a deep auto-encoder to extract the defining feature of adaptive structures automatically. The results in the case of no ecological inheritance revealed that the number of available resources can affect the diversity of emerging adaptive structures. Also, in the case with ecological inheritance, it was found that combinations of two types of ecological inheritance, which are the inheritance of adaptive structures and birthplace, can have strong effects on the diversity of emerging structures and the adaptivity of the population. We expect that findings in evolutionary simulations of niche-constructing behavior might contribute to evolutionary design of robotic builders or robot fabrication, especially when we assume physically simulated environments.

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Crossref · 10.3389/frobt.2020.00045

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Figures

Figure 1 The field for fitness evaluation.
Figure 1 The field for fitness evaluation.CC BY · PubMed Central
Figure 2 The neural network of a prey.
Figure 2 The neural network of a prey.CC BY · PubMed Central
Figure 3 The structures of deep auto encoder.
Figure 3 The structures of deep auto encoder.CC BY · PubMed Central
Figure 4 An interface for manual classification of adaptive structures on the feature space.
Figure 4 An interface for manual classification of adaptive structures on the feature space.CC BY · PubMed Central
Figure 5 The fitness and the maximum number of objects B in the case of no ecological inheritance. Symbols denote statistical comparisons of the fitness between cases of B using the Wilcoxon rank sum test.
Figure 5 The fitness and the maximum number of objects B in the case of no ecological inheritance. Symbols denote statistical comparisons of the fitness between cases of B using the Wilcoxon rank sum test.CC BY · PubMed Central
Figure 6 The typical strategies which evolved in our model. (A) Shell strategy, (B) barnacles strategy, (C) wall strategy, (D) complex structure (P = True and W = 0.1), and (E) complex structure (P = True and W = 1.0).
Figure 6 The typical strategies which evolved in our model. (A) Shell strategy, (B) barnacles strategy, (C) wall strategy, (D) complex structure (P = True and W = 0.1), and (E) complex structure (P = True and W = 1.0).CC BY · PubMed Central
Figure 7 The feature plot of adaptive structures in the case without ecological inheritance.
Figure 7 The feature plot of adaptive structures in the case without ecological inheritance.CC BY · PubMed Central
Figure 8 The feature plot of adaptive structures colored by the parameter setting of the maximum number of objects B in the case of no ecological inheritance.
Figure 8 The feature plot of adaptive structures colored by the parameter setting of the maximum number of objects B in the case of no ecological inheritance.CC BY · PubMed Central
Figure 9 The feature plot of adaptive structures colored by the x-coordinate of COM of each adaptive structure in the case of no ecological inheritance.
Figure 9 The feature plot of adaptive structures colored by the x-coordinate of COM of each adaptive structure in the case of no ecological inheritance.CC BY · PubMed Central
Figure 10 The result of manual classification of adaptive structures in the case of no ecological inheritance.
Figure 10 The result of manual classification of adaptive structures in the case of no ecological inheritance.CC BY · PubMed Central
Figure 11 The number of adaptive structures of each strategy in the case of no ecological inheritance.
Figure 11 The number of adaptive structures of each strategy in the case of no ecological inheritance.CC BY · PubMed Central
Figure 12 The fitness (y-axis) and the maximum number of objects B (x-axis) in the case of ecological inheritance. Symbols denote statistical comparisons of the fitness between possible cases of ecological inheritance (W and P) using the Wilcoxon rank sum test. We aggregated values of the fitness among all conditions of B for each case of ecological inheritance, and conducted the test on the aggregated fitness values. (A) W = 1.0, P = False; (B) W = 0.1, P = False; (C) W = 0.01, P = False; (D) W = 1.0, P = True; (E) W = 0.1, P = True; and (F) W = 0.01, P = True.
Figure 12 The fitness (y-axis) and the maximum number of objects B (x-axis) in the case of ecological inheritance. Symbols denote statistical comparisons of the fitness between possible cases of ecological inheritance (W and P) using the Wilcoxon rank sum test. We aggregated values of the fitness among all conditions of B for each case of ecological inheritance, and conducted the test on the aggregated fitness values. (A) W = 1.0, P = False; (B) W = 0.1, P = False; (C) W = 0.01, P = False; (D) W = 1.0, P = True; (E) W = 0.1, P = True; and (F) W = 0.01, P = True.CC BY · PubMed Central
Figure 13 The results of manual classification in the case of inheritance of the birthplace. (A) W = 1.0, (B) W = 0.1 and (C) W = 0.01.
Figure 13 The results of manual classification in the case of inheritance of the birthplace. (A) W = 1.0, (B) W = 0.1 and (C) W = 0.01.CC BY · PubMed Central

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  1. Chiba, 2016, How ecological inheritance can affect the evolution of complex niche construction in a 2D physical simulation, 426

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Metadata

Authors
Chiba, N., Suzuki, R., & Arita, T.
Affiliations
Nagoya University (JP)
Corresponding author
  • Chiba, Naoaki
  • Suzuki, Reiji
ORCID
Venue
Frontiers in Robotics and AI
Publisher
Frontiers Media SA
Published
2020-04-09
Volume
7
Pages
45-45
ISSN
2296-9144 (ISSN-L)
DOI
10.3389/frobt.2020.00045
PMC
PMC7805702
OpenAlex
W3015907216
Cited by
5
References
25
Citations by year
2026: 1 · 2025: 1 · 2024: 1 · 2023: 1 · 2021: 1
FWCI
0.20
Type
journal article
Language
en
Open access
Licence
Locations
  • Frontiers in Robotics and AI (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
Japan Society for the Promotion of Science (JP17H06383 in #4903, JP18K11467, JP19K12137)
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › Evolutionary Algorithms and Applications
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Evolution and Genetic Dynamics
  • Physical Sciences › Engineering › Mechanical Engineering › Modular Robots and Swarm Intelligence
Keywords
niche construction, ecological inheritance, predator-prey interactions, adaptive structures, open-ended evolution, resource availability, structural diversity, robotic fabrication, embodied agents

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CoChat. (2026). Citation check: Evolution of Complex Niche-Constructing Behaviors and Ecological Inheritance of Adaptive Structures in a Physically Grounded Environment. https://app.cochat.ai/papers/10.3389/frobt.2020.00045
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Chiba, N., Suzuki, R., & Arita, T. (2020). Evolution of Complex Niche-Constructing Behaviors and Ecological Inheritance of Adaptive Structures in a Physically Grounded Environment. Frontiers in Robotics and AI. https://doi.org/10.3389/frobt.2020.00045