Research reading 100 / Actors / 2022
Design of simulation-based pilot training systems using machine learning agents
Source authors: J. Källström; R. Granlund; F. Heintz
Originally published in The Aeronautical Journal · 2022
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Design of simulation-based pilot training systems using machine learning agents
J. Källström; R. Granlund; F. Heintz
The guide and its evidence limits are journal annotations, not quotations from the original researchers. The complete original paper is not currently in this agent’s searchable context.
A4 Synthetic actors and human–AI teams
Why read this for flight training?
Investigates capabilities required of learning agents in simulation-based training. A central actor-layer reading for realistic, useful synthetic participants.
How to interpret the evidence
Domain analysis and experiments do not establish that automated agents can replace instructors across training contexts.
Screening basis: Abstract screened. This annotation identifies relevance and limits; it does not replace appraisal of the original methods and findings.
Cite the original article
J. Källström; R. Granlund; F. Heintz (2022). Design of simulation-based pilot training systems using machine learning agents. The Aeronautical Journal, 126(1300), 907-931. https://doi.org/10.1017/aer.2022.8
Publication record
The original paper retains its published authors, venue and DOI. This journal’s reading guide was prepared with AI assistance under the editorial direction of Dr. Freedom Cheteni. The source authors are not credited as authors of this annotation. No new peer review or DOI is claimed for the guide.
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