Search results for "Opinion Dynamics"

showing 8 items of 8 documents

Distance-constrained data clustering by combined k-means algorithms and opinion dynamics filters

2014

Data clustering algorithms represent mechanisms for partitioning huge arrays of multidimensional data into groups with small in–group and large out–group distances. Most of the existing algorithms fail when a lower bound for the distance among cluster centroids is specified, while this type of constraint can be of help in obtaining a better clustering. Traditional approaches require that the desired number of clusters are specified a priori, which requires either a subjective decision or global meta–information knowledge that is not easily obtainable. In this paper, an extension of the standard data clustering problem is addressed, including additional constraints on the cluster centroid di…

Fuzzy clusteringCorrelation clusteringSingle-linkage clusteringConstrained clusteringcomputer.software_genreDetermining the number of clusters in a data setSettore ING-INF/04 - AutomaticaData clustering k–means Opinion dynamics Hegelsmann–Krause modelCURE data clustering algorithmData miningCluster analysisAlgorithmcomputerk-medians clusteringMathematics22nd Mediterranean Conference on Control and Automation
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Complex Networked Systems: Convergence Analysis, Dynamic Behaviour, and Security.

Complex networked systems are a modern reference framework through which very dierent systems from far disciplines, such as biology, computer science, physics, social science, and engineering, can be described. They arise in the great majority of modern technological applications. Examples of real complex networked systems include embedded systems, biological networks, large-scale systems such as power generation grids, transportation networks, water distribution systems, and social network. In the recent years, scientists and engineers have developed a variety of techniques, approaches, and models to better understand and predict the behaviour of these systems, even though several research…

Complex Network Data clustering Hegselmann-Krause model Consensus Security Attacks Line Network k-means Opinion Dynamics.Settore ING-INF/04 - Automatica
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Opinion dynamics, stubbornness and mean-field games

2014

This paper studies opinion dynamics and stubbornness using mean-field game theory. Assuming an initial exponential density function and affine control policies we analyze under what conditions the Fokker-Planck equation returns an exponential density function over the horizon. Consensus and clusters formation are also studied.

mean-field games; optimal controlFunction (mathematics)Exponential densitymean-field gamesoptimal controlSettore ING-INF/04 - AutomaticaOpinion dynamicsMean field theoryApplied mathematicsAffine transformationSettore MAT/09 - Ricerca OperativaMathematical economicsGame theoryMathematics53rd IEEE Conference on Decision and Control
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Opinion dynamics in coalitional games with transferable utilities

2014

This paper studies opinion dynamics in a large number of homogeneous coalitional games with transferable utilities (TU), where the characteristic function is a continuous-time stochastic process. For each game, which we can see as a “small world”, the players share opinions on how to allocate revenues based on the mean-field interactions with the other small worlds. As a result of such mean-field interactions among small worlds, in each game, a central planner allocates revenues based on the extra reward that a coalition has received up to the current time and the extra reward that the same coalition has received in the other games. The paper also studies the convergence and stability of op…

Characteristic function (convex analysis)Opinion dynamicsStochastic processComputer scienceStability (learning theory)RevenueConvergence (relationship)Mathematical economics53rd IEEE Conference on Decision and Control
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Opinion dynamics and stubbornness through mean-field games

2013

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.

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 theoryMathematics
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Opinion dynamics in social networks through mean field games

2016

Emulation, mimicry, and herding behaviors are phenomena that are observed when multiple social groups interact. To study such phenomena, we consider in this paper a large population of homogeneous social networks. Each such network is characterized by a vector state, a vector-valued controlled input, and a vector-valued exogenous disturbance. The controlled input of each network aims to align its state to the mean distribution of other networks' states in spite of the actions of the disturbance. One of the contributions of this paper is a detailed analysis of the resulting mean-field game for the cases of both polytopic and $mathcal L_2$ bounds on controls and disturbances. A second contrib…

0209 industrial biotechnologyeducation.field_of_studyControl and OptimizationDisturbance (geology)Applied MathematicsPopulation020206 networking & telecommunications02 engineering and technologyState (functional analysis)020901 industrial engineering & automationMean field theoryControl theoryBellman equationConvergence (routing)0202 electrical engineering electronic engineering information engineeringSpiteHerdingOpinion DynamicsSettore MAT/09 - Ricerca OperativaeducationMathematics
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Mean-Field Game Modeling the Bandwagon Effect with Activation Costs

2015

This paper provides a mean-field game theoretic model of the bandwagon effect in social networks. This effect can be observed whenever individuals tend to align their own opinions to a mainstream opinion. The contribution is threefold. First, we describe the opinion propagation as a mean-field game with local interactions. Second, we establish mean-field equilibrium strategies in the case where the mainstream opinion is constant. Such strategies are shown to have a threshold structure. Third, we extend the use of threshold strategies to the case of time-varying mainstream opinion and study the evolution of the macroscopic system.

Physics::Physics and SocietyStatistics and Probability0209 industrial biotechnologyEconomics and Econometrics02 engineering and technologyMean-field gamesMean field gameActivation costs; Bandwagon effect; Games with infinitely many players; Mean-field games; Mode; Threshold policies;01 natural sciencesActivation costs010305 fluids & plasmasMicroeconomics020901 industrial engineering & automationOpinion dynamicsGames with infinitely many players; Bandwagon effect; Activation costs; Threshold policies; Mean-field games; ModeMean-field game0103 physical sciencesEconomicsThreshold policiesMainstreamBandwagon effectStructure (mathematical logic)Game theoreticApplied MathematicsMode (statistics)Computer Science::Social and Information NetworksComputer Graphics and Computer-Aided DesignComputer Science ApplicationsComputational MathematicsActivation costComputational Theory and MathematicsGames with infinitely many playersGames with infinitely many playerModeSettore MAT/09 - Ricerca OperativaConstant (mathematics)Threshold policieMathematical economicsBandwagon effectDynamic Games and Applications
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Opinion Dynamics and Stubbornness via Multi-Population Mean-Field Games

2016

This paper studies opinion dynamics for a set of heterogeneous populations of individuals pursuing two conflicting goals: to seek consensus and to be coherent with their initial opinions. The multi-population game under investigation is characterized by (i) rational agents who behave strategically, (ii) heterogeneous populations, and (iii) opinions evolving in response to local interactions. The main contribution of this paper is to encompass all of these aspects under the unified framework of mean-field game theory. We show that, assuming initial Gaussian density functions and affine control policies, the Fokker---Planck---Kolmogorov equation preserves Gaussianity over time. This fact is t…

0209 industrial biotechnologyMathematical optimizationConsensusControl and OptimizationHeterogeneous populationsPopulationOpinion dynamics Consensus Heterogeneous populations Stubbornness Mean-field games02 engineering and technologyMean-field gamesManagement Science and Operations Research01 natural sciences020901 industrial engineering & automationSettore ING-INF/04 - AutomaticaStubbornness0101 mathematicseducationSet (psychology)Opinion dynamicsFinite setMathematicseducation.field_of_studyStochastic processApplied MathematicsOpinion dynamics Consensus Heterogeneous populations Stubbornness Mean-field gamesRational agentOptimal control010101 applied mathematicsTheory of computationSettore MAT/09 - Ricerca OperativaGame theory
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