Physics Department, University of Miami, Coral Gables, FL 33126, USA.
College of Physics, Optoelectronics and Energy, Soochow University, Suzhou 215006, China.
Sci Adv. 2019 Feb 6;5(2):eaau5902. doi: 10.1126/sciadv.aau5902. eCollection 2019 Feb.
Understanding how systems with many semi-autonomous parts reach a desired target is a key question in biology (e.g., 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.
理解具有许多半自主部分的系统如何达到期望的目标是生物学（例如，幼虫寻找食物）、工程学（例如，无人驾驶导航）、医学（例如，脑损伤患者的可靠运动）和社会经济学（例如，自下而上的目标驱动的人类组织）中的一个关键问题。集中式系统具有更好的组件，其性能会更好。相比之下，我们通过对比表明，当组成部分的能力较低时，分散式实体更能有效地达到目标。我们的研究结果再现了生物体的实验结果，预测了自动驾驶汽车的组件越简单，其性能可能越好，为生物进化为何从分散式设计跳跃到集中式设计提供了新的解释，为尽管中枢功能受损但仍能实现高效运动提供了思路，并提供了一个预测系统组件最佳能力的公式，以便其尽可能接近目标或目标。
