Evidence map›Paper›PMID 35252363›Full record

ArticleFrontiers in robotics and AI2022

Characterization of Indicators for Adaptive Human-Swarm Teaming.

Aya Hussein, Leo Ghignone, Tung Nguyen, Nima Salimi, Hung Nguyen, Min Wang, Hussein A Abbass

Abstract read
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In one paragraph

Article in Frontiers in robotics and AI, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
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

7 authors.

Aya HusseinSchool of Engineering and Information Technology, University of New South Wales, Canberra, ACT, Australia.
Leo GhignoneSchool of Engineering and Information Technology, University of New South Wales, Canberra, ACT, Australia.
Tung NguyenSchool of Engineering and Information Technology, University of New South Wales, Canberra, ACT, Australia.
Nima SalimiSchool of Engineering and Information Technology, University of New South Wales, Canberra, ACT, Australia.
Hung NguyenSchool of Engineering and Information Technology, University of New South Wales, Canberra, ACT, Australia.
Min WangSchool of Engineering and Information Technology, University of New South Wales, Canberra, ACT, Australia.
Hussein A AbbassSchool of Engineering and Information Technology, University of New South Wales, Canberra, ACT, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Swarm systems consist of large numbers of agents that collaborate autonomously. With an appropriate level of human control, swarm systems could be applied in a variety of contexts ranging from urban search and rescue situations to cyber defence. However, the successful deployment of the swarm in such applications is conditioned by the effective coupling between human and swarm. While adaptive autonomy promises to provide enhanced performance in human-machine interaction, distinct factors must be considered for its implementation within human-swarm interaction. This paper reviews the multidisciplinary literature on different aspects contributing to the facilitation of adaptive autonomy in human-swarm interaction. Specifically, five aspects that are necessary for an adaptive agent to operate properly are considered and discussed, including mission objectives, interaction, mission complexity, automation levels, and human states. We distill the corresponding indicators in each of the five aspects, and propose a framework, named MICAH (i.e., Mission-Interaction-Complexity-Automation-Human), which maps the primitive state indicators needed for adaptive human-swarm teaming.

Indexed as

adaptive autonomyautomation indicatorscomplexity indicatorshuman cognitive state assessmenthuman-swarm interactioninteraction indicatorsmission performance indicators

Identifiers

PMID35252363
PMCPMC8891141

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.