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Nonlinear Network Dynamics for Bio-Inspired Collective Decision-Making

用于仿生集体决策的非线性网络动力学

基本信息

批准号：
1635056
负责人：
Naomi Leonard
金额：
$ 40万
依托单位：
Princeton University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2016
资助国家：
美国
起止时间：
2016-09-01 至 2020-08-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1635056&HistoricalAwards=false
关键词：
Nonlinear Network Dynamics Bio Inspired

项目摘要

This project will build upon model-based investigation of group decision-making in animals, to create a rigorous methodology for bio-inspired control of multi-agent systems. It is well known that bird flocks and fish schools show a remarkable ability to choose between mutually exclusive competing options with speed, accuracy, robustness and adaptability. This project will derive a general and flexible framework for modeling collective decision making, by applying singularity and bifurcation theory to graph-based representations of the dynamics of networked systems. The mathematical framework will be validated on experimental data from observations of swarming honeybees and schooling fish. The resulting methodology will find application to design and control of, for example, mobile sensing networks, transportation networks, and power networks. These applications have significant potential societal impact in environmental monitoring, hazard response, transportation, energy, healthcare, and manufacturing. Leveraging this exciting, cross-disciplinary topic, the project will engage middle and high school girls through researcher visits into schools, and student and teacher visits to the Principle Investigator's lab.An analytically tractable, abstract agent-based model for collective decision-making dynamics that captures nonlinear phenomena observed in animal groups will be used. This will enable a new methodology for coordinated decision-making that extends current capabilities of networks of dynamic agents to reliably perform demanding tasks in complex, changing environments. A principled approach, based on singularity theory -- a robust bifurcation theory -- will be used for this model to connect biology to engineering design. Realizations of collective decision-making between alternatives will be derived and conditions for high performance proved by building in value-sensitive decision-making and addressing heterogeneity in preferences across the group. Explorations will go beyond biologically plausible parameter ranges to identify and prove conditions for high-performing engineered collective decision-making dynamics.

该项目将建立在基于模型的动物群体决策研究的基础上，为多智能体系统的生物启发控制创建一个严格的方法。众所周知，鸟群和鱼群表现出非凡的能力，能够在相互排斥的竞争选项之间进行选择，具有速度、准确性、鲁棒性和适应性。本项目将通过将奇异性和分叉理论应用于网络系统动态的图形表示，推导出一个通用和灵活的集体决策建模框架。该数学框架将验证的实验数据，从观察蜂群蜜蜂和学校的鱼。所得到的方法将找到应用程序的设计和控制，例如，移动的传感网络，交通网络和电力网络。这些应用在环境监测、灾害响应、交通、能源、医疗保健和制造业方面具有重大的潜在社会影响。利用这个令人兴奋的，跨学科的主题，该项目将通过研究人员访问学校，学生和教师访问首席研究员的实验室，吸引初中和高中女生。将使用一个易于分析的，抽象的基于代理的集体决策动态模型，捕捉动物群体中观察到的非线性现象。这将为协调决策提供一种新的方法，扩展动态代理网络的当前能力，以便在复杂、不断变化的环境中可靠地执行要求苛刻的任务。一个原则性的方法，基于奇点理论-一个强大的分叉理论-将用于这个模型连接生物学工程设计。将通过建立对价值敏感的决策和解决整个群体偏好的异质性，推导出备选方案之间的集体决策的实现，并证明高绩效的条件。探索将超越生物学上合理的参数范围，以确定和证明高性能工程集体决策动态的条件。

项目成果

期刊论文数量（6）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Active Control and Sustained Oscillations in actSIS Epidemic Dynamics

actSIS 流行动态中的主动控制和持续振荡

DOI：
发表时间：
2020
期刊：
3rd IFAC Workshop on Cyber-Physical & Human Systems
影响因子：
0
作者：
Zhou, Yunxiu;Levin, Simon A.;Leonard, Naomi Ehrich
通讯作者：
Leonard, Naomi Ehrich

Stability-Flexibility Dilemma in Cognitive Control: A Dynamical System Perspective

DOI：
发表时间：
2019
期刊：
影响因子：
0
作者：
Sebastian Musslick;Anastasia S. Bizyaeva;Shamay Agaron;Naomi Ehrich Leonard;J. Cohen
通讯作者：
Sebastian Musslick;Anastasia S. Bizyaeva;Shamay Agaron;Naomi Ehrich Leonard;J. Cohen

Bio-inspired decision-making and control: From honeybees and neurons to network design