@article{fb5fcb4d3e7342129ea9fbaf8dfba950,
title = "Neuro-Inspired Dynamic Replanning in Swarms- Theoretical Neuroscience Extends Swarming in Complex Environments",
abstract = "In the NeuroSwarms framework, a team including researchers from the Johns Hopkins University Applied Physics Laboratory (APL) and the Johns Hopkins University School of Medicine (JHM) applied key theoretical concepts from neuroscience to models of distributed multi-agent autonomous systems and found that complex swarming behaviors arise from simple learning rules used by the mammalian brain.",
author = "Hwang, {Grace M.} and Schultz, {Kevin M.} and Monaco, {Joseph D.} and Kechen Zhang",
note = "Funding Information: ACKNOWLEDGMENTS: This material is based on work supported by (while serving at) the National Science Foundation. Any opinion, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation. This work was supported by National Science Foundation Award NCS/FO 1835279, APL independent research and development awards, and the Johns Hopkins University Kavli Neuroscience Discovery Institute. Publisher Copyright: {\textcopyright} 2021 John Hopkins University. All rights reserved.",
year = "2021",
language = "English (US)",
volume = "35",
pages = "443--447",
journal = "Johns Hopkins APL Technical Digest (Applied Physics Laboratory)",
issn = "0270-5214",
publisher = "John Hopkins University Press",
number = "4",
}