6533b853fe1ef96bd12ad797
RESEARCH PRODUCT
Opinion dynamics and stubbornness through mean-field games
Fabio BagagioloDario BausoGiacomo ComoLeonardo Stellasubject
education.field_of_studyPartial differential equationControl and OptimizationDifferential equationMulti-agent systemPopulationComputer Science::Social and Information NetworksControl and Systems Engineering; Modeling and Simulation; Control and OptimizationInterpretation (model theory)Computer Science::Multiagent SystemsStochastic partial differential equationMean field theoryComputer Science::Systems and ControlControl and Systems EngineeringModeling and Simulationopinion dynamicseducationMathematical economicsGame theoryMathematicsdescription
This paper provides a mean field game theoretic interpretation of opinion dynamics and stubbornness. The model describes a crowd-seeking homogeneous population of agents, under the influence of one stubborn agent. The game takes on the form of two partial differential equations, the Hamilton-Jacobi-Bellman equation and the Kolmogorov-Fokker-Planck equation for the individual optimal response and the population evolution, respectively. For the game of interest, we establish a mean field equilibrium where all agents reach epsilon-consensus in a neighborhood of the stubborn agent's opinion.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2013-12-01 |