OpenAI single-agent LLM architecture reduces computational overhead relative to multi-agent orchestration in a simulated mars rover decision-support benchmark.
- DOI
- 10.3389/frobt.2026.1877762
- Published
- 2026
- Container
- Frontiers in robotics and AI
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.3389/frobt.2026.1877762,
title = {OpenAI single-agent LLM architecture reduces computational overhead relative to multi-agent orchestration in a simulated mars rover decision-support benchmark.},
author = {Sanabria D},
year = {2026},
journal = {Frontiers in robotics and AI},
doi = {10.3389/frobt.2026.1877762},
url = {https://doi.org/10.3389/frobt.2026.1877762}
}RIS
TY - JOUR TI - OpenAI single-agent LLM architecture reduces computational overhead relative to multi-agent orchestration in a simulated mars rover decision-support benchmark. AU - Sanabria D PY - 2026 JO - Frontiers in robotics and AI DO - 10.3389/frobt.2026.1877762 UR - https://doi.org/10.3389/frobt.2026.1877762 ER -
APA
D, S. (2026). OpenAI single-agent LLM architecture reduces computational overhead relative to multi-agent orchestration in a simulated mars rover decision-support benchmark.. Frontiers in robotics and AI. https://doi.org/10.3389/frobt.2026.1877762
Source records
- pubmed · retrieved 2026-11-10T10:38:13.633Z