Abstract
Understanding how systems with many semi-autonomous parts reach a desired target is a key question in biology (e.g., Drosophila larvae seeking food), engineering (e.g., driverless navigation), medicine (e.g., reliable movement for brain-damaged individuals), and socioeconomics (e.g., bottom-up goal-driven human organizations). Centralized systems perform better with better components. Here, we show, by contrast, that a decentralized entity is more efficient at reaching a target when its components are less capable. Our findings reproduce experimental results for a living organism, predict that autonomous vehicles may perform better with simpler components, offer a fresh explanation for why biological evolution jumped from decentralized to centralized design, suggest how efficient movement might be achieved despite damaged centralized function, and provide a formula predicting the optimum capability of a system’s components so that it comes as close as possible to its target or goal.
| Original language | English (US) |
|---|---|
| Article number | eaau5902 |
| Journal | Science Advances |
| Volume | 5 |
| Issue number | 2 |
| DOIs | |
| State | Published - Feb 6 2019 |
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ASJC Scopus subject areas
- General
- Physics and Astronomy (miscellaneous)
Cite this
Getting closer to the goal by being less capable. / Manrique, Pedro D.; Klein, Mason; Li, Yao Sheng; Xu, Chen; Hui, Pak Ming; Johnson, Neil F.
In: Science Advances, Vol. 5, No. 2, eaau5902, 06.02.2019.Research output: Contribution to journal › Article
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TY - JOUR
T1 - Getting closer to the goal by being less capable
AU - Manrique, Pedro D.
AU - Klein, Mason
AU - Li, Yao Sheng
AU - Xu, Chen
AU - Hui, Pak Ming
AU - Johnson, Neil F.
PY - 2019/2/6
Y1 - 2019/2/6
N2 - Understanding how systems with many semi-autonomous parts reach a desired target is a key question in biology (e.g., Drosophila larvae seeking food), engineering (e.g., driverless navigation), medicine (e.g., reliable movement for brain-damaged individuals), and socioeconomics (e.g., bottom-up goal-driven human organizations). Centralized systems perform better with better components. Here, we show, by contrast, that a decentralized entity is more efficient at reaching a target when its components are less capable. Our findings reproduce experimental results for a living organism, predict that autonomous vehicles may perform better with simpler components, offer a fresh explanation for why biological evolution jumped from decentralized to centralized design, suggest how efficient movement might be achieved despite damaged centralized function, and provide a formula predicting the optimum capability of a system’s components so that it comes as close as possible to its target or goal.
AB - Understanding how systems with many semi-autonomous parts reach a desired target is a key question in biology (e.g., Drosophila larvae seeking food), engineering (e.g., driverless navigation), medicine (e.g., reliable movement for brain-damaged individuals), and socioeconomics (e.g., bottom-up goal-driven human organizations). Centralized systems perform better with better components. Here, we show, by contrast, that a decentralized entity is more efficient at reaching a target when its components are less capable. Our findings reproduce experimental results for a living organism, predict that autonomous vehicles may perform better with simpler components, offer a fresh explanation for why biological evolution jumped from decentralized to centralized design, suggest how efficient movement might be achieved despite damaged centralized function, and provide a formula predicting the optimum capability of a system’s components so that it comes as close as possible to its target or goal.
UR - http://www.scopus.com/inward/record.url?scp=85061304134&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85061304134&partnerID=8YFLogxK
U2 - 10.1126/sciadv.aau5902
DO - 10.1126/sciadv.aau5902
M3 - Article
C2 - 30775434
AN - SCOPUS:85061304134
VL - 5
JO - Indian Journal of Pure and Applied Physics
JF - Indian Journal of Pure and Applied Physics
SN - 0019-5596
IS - 2
M1 - eaau5902
ER -