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Nonlinear Opinion Dynamics With Tunable Sensitivity
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DOI：10.1109/TAC.2022.3159527.png)
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摘要
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We propose a continuous-time multioption nonlinear generalization of classical linear weighted-average opinion dynamics. Nonlinearity is introduced by saturating opinion exchanges, and this is enough to enable a significantly greater range of opinion-forming behaviors with our model as compared to existing linear and nonlinear models. For a group of agents that communicate opinions over a network, these behaviors include multistable agreement and disagreement, tunable sensitivity to input, robustness to disturbance, flexible transition between patterns of opinions, and opinion cascades. We derive network-dependent tuning rules to robustly control the system behavior and we design state-feedback dynamics for the model parameters to make the behavior adaptive to changing external conditions. The model provides new means for systematic study of dynamics on natural and engineered networks, from information spread and political polarization to collective decision-making and dynamic task allocation.
Keyword:
Sensitivity
Analytical models
Adaptation models
Aerodynamics
Robustness
Dynamic scheduling
Biological system modeling
Agreement
bifurcation
bio-inspired engineering
deadlock breaking
decision making
disagreement
multi-agent systems
network centrality
networked control systems
nonlinear dynamical systems
opinion dynamics
期刊
IF:
7
论文数:
1.3W
被引数:
6.7W
机构
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