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.
N1 - Funding Information:
N.F.J. acknowledges funding from the NSF grant CNS1522693 and Air Force (AFOSR) grant FA9550-16-1-0247.
Publisher Copyright:
Copyright © 2019 The Authors.
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.
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U2 - 10.1126/sciadv.aau5902
DO - 10.1126/sciadv.aau5902
M3 - Article
C2 - 30775434
AN - SCOPUS:85061304134
VL - 5
JO - Science advances
JF - Science advances
SN - 2375-2548
IS - 2
M1 - eaau5902
ER -