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Cited by 122Complex Systems and DynamicsModular Robots and Swarm IntelligenceGene Regulatory Network Analysis

Collective intelligence: a unifying concept for integrating biology across scales and substrates

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McMillen, Patrick, Levin, Michael·2024·Communications Biology
DOI 10.1038/s42003-024-06037-4PMC PMC10978875
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Abstract

A defining feature of biology is the use of a multiscale architecture, ranging from molecular networks to cells, tissues, organs, whole bodies, and swarms. Crucially however, biology is not only nested structurally, but also functionally: each level is able to solve problems in distinct problem spaces, such as physiological, morphological, and behavioral state space. Percolating adaptive functionality from one level of competent subunits to a higher functional level of organization requires collective dynamics: multiple components must work together to achieve specific outcomes. Here we overview a number of biological examples at different scales which highlight the ability of cellular material to make decisions that implement cooperation toward specific homeodynamic endpoints, and implement collective intelligence by solving problems at the cell, tissue, and whole-organism levels. We explore the hypothesis that collective intelligence is not only the province of groups of animals, and that an important symmetry exists between the behavioral science of swarms and the competencies of cells and other biological systems at different scales. We then briefly outline the implications of this approach, and the possible impact of tools from the field of diverse intelligence for regenerative medicine and synthetic bioengineering.

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  • The scope of problem-solving and decision-making expands with scaling up layers of complexity-consistent with the concept of cognitive domains.

    “Regardless of the epistemological lens, what matters is that the scope of problem-solving and decision-making expands—consistent with the concept of cognitive domains, as emphasized also by others (e.g., McMillen and Levin, 2024).”

    From Wetware network-based AI: a chemical approach to embodied cognition for robotics and artificial intelligence (2026) · cites this paper as McMillen and Levin, 2024

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200 of 218 shown

Cited by

Sorted by citations

Authors
McMillen, P., & Levin, M.
Affiliations
Tufts University (US)
Corresponding author
Levin, Michael
ORCID
Levin, Michael
Venue
Communications Biology
Publisher
Springer Science and Business Media LLC
Published
2024-03-28
Volume
7
Issue
1
Pages
378-378
ISSN
2399-3642 (ISSN-L)
DOI
10.1038/s42003-024-06037-4
PMC
PMC10978875
OpenAlex
W4393280006
Cited by
122
References
14
Citations by year
2026: 49 · 2025: 51 · 2024: 22
FWCI
2.88
Type
journal article
Language
en
Open access
Licence
Locations
  • Communications Biology (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • John Templeton Foundation (62212, 62230)
  • Templeton World Charity Foundation (TWCF0606)
Topics
  • Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Complex Systems and Dynamics
  • Physical Sciences › Engineering › Mechanical Engineering › Modular Robots and Swarm Intelligence
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
Keywords
collective intelligence, biological swarms, collective dynamics, cellular decision-making, homeostasis, regenerative medicine
MeSH terms
Animals, Biology, Intelligence, Problem Solving, Regenerative Medicine, Bioengineering

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