Evidence map›Paper›PMID 38653192›Full record

ReviewAdvanced materials (Deerfield Beach, Fla.)2025

Swarm Autonomy: From Agent Functionalization to Machine Intelligence.

Yibin Wang, Hui Chen, Leiming Xie, Jinbo Liu, Li Zhang, Jiangfan Yu

Abstract readReview
In one paragraph

Review in Advanced materials (Deerfield Beach, Fla.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

18 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Review
  6. Collective behavior of "flexicles".Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  7. Collective Dynamics of Urease-Based Nanomotors in a Chemical Gradient.Small (Weinheim an der Bergstrasse, Germany) · 2025
    Article
  8. Review
  9. Article
  10. Metareview: a survey of active matter reviews.The European physical journal. E, Soft matter · 2025
    Review
  11. Review
  12. Signalling and social learning in swarms of robots.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2025
    Article
  13. Advanced Imaging Strategies Based on Intelligent Micro/Nanomotors.Cyborg and bionic systems (Washington, D.C.) · 2025
    Review
  14. Review
  15. Swarm Autonomy: From Agent Functionalization to Machine Intelligence.Advanced materials (Deerfield Beach, Fla.) · 2025
    Review
  16. Microrobotic Swarms for Cancer Therapy.Research (Washington, D.C.) · 2025
    Review
  17. Article
  18. Swarming Magnetic FeResearch (Washington, D.C.) · 2024
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Yibin WangSchool of Science and Engineering, The Chinese University of Hong Kong, Shenzhen, 518172, China.ORCID https://orcid.org/0000-0003-4361-606X
Hui ChenSchool of Science and Engineering, The Chinese University of Hong Kong, Shenzhen, 518172, China.
Leiming XieSchool of Science and Engineering, The Chinese University of Hong Kong, Shenzhen, 518172, China.
Jinbo LiuSchool of Science and Engineering, The Chinese University of Hong Kong, Shenzhen, 518172, China.
Li ZhangDepartment of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Hong Kong, 999077, China.
Jiangfan YuSchool of Science and Engineering, The Chinese University of Hong Kong, Shenzhen, 518172, China.ORCID https://orcid.org/0000-0002-7981-6744

Funding

Guangdong Basic and Applied Basic Research Foundation 2022A1515110499National Key R&D Program of China 2022YFA1207100National Natural Science Foundation of China 62103347Shenzhen Institute of Artificial Intelligence and Robotics for Society AC01202201007-03
6 · The paper itself

Abstract

Swarm behaviors are common in nature, where individual organisms collaborate via perception, communication, and adaptation. Emulating these dynamics, large groups of active agents can self-organize through localized interactions, giving rise to complex swarm behaviors, which exhibit potential for applications across various domains. This review presents a comprehensive summary and perspective of synthetic swarms, to bridge the gap between the microscale individual agents and potential applications of synthetic swarms. It is begun by examining active agents, the fundamental units of synthetic swarms, to understand the origins of their motility and functionality in the presence of external stimuli. Then inter-agent communications and agent-environment communications that contribute to the swarm generation are summarized. Furthermore, the swarm behaviors reported to date and the emergence of machine intelligence within these behaviors are reviewed. Eventually, the applications enabled by distinct synthetic swarms are summarized. By discussing the emergent machine intelligence in swarm behaviors, insights are offered into the design and deployment of autonomous synthetic swarms for real-world applications.

Indexed as

active matterautonomymachine intelligencemicrorobotsswarm behavior

Identifiers

PMID38653192
PMCPMC11733729

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.