6 research outputs found
Opinion dynamics and stubbornness through mean-field games
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 "-consensus in a neighborhood of the stubborn agent's opinion. ©2013 IEEE
Hydrodynamic models of preference formation in multi-agent societies
In this paper, we discuss the passage to hydrodynamic equations for kinetic
models of opinion formation. The considered kinetic models feature an opinion
density depending on an additional microscopic variable, identified with the
personal preference. This variable describes an opinion-driven polarisation
process, leading finally to a choice among some possible options, as it happens
e.g. in referendums or elections. Like in the kinetic theory of rarefied gases,
the derivation of hydrodynamic equations is essentially based on the
computation of the local equilibrium distribution of the opinions from the
underlying kinetic model. Several numerical examples validate the resulting
model, shedding light on the crucial role played by the distinction between
opinion and preference formation on the choice processes in multi-agent
societies.Comment: 30 pages, 15 figure
Mean-Field-Type Games in Engineering
A mean-field-type game is a game in which the instantaneous payoffs and/or
the state dynamics functions involve not only the state and the action profile
but also the joint distributions of state-action pairs. This article presents
some engineering applications of mean-field-type games including road traffic
networks, multi-level building evacuation, millimeter wave wireless
communications, distributed power networks, virus spread over networks, virtual
machine resource management in cloud networks, synchronization of oscillators,
energy-efficient buildings, online meeting and mobile crowdsensing.Comment: 84 pages, 24 figures, 183 references. to appear in AIMS 201