Game theory has long served as a framework with which to model interactive decision making for scenarios where agents are motivated to maximize their individual welfare. However, when agents are influenced by the opinions and attitudes of others, the opportunity exists to make coordinated decisions in the pursuit of systematic group behavior. The application of conditional game theory, Bayesian network theory, and Markov convergence theory provides a framework within which to formalize a theory of coordinated decision making under social influence.

Coordinated Distributed Decision Making on Social Influence Networks

Tummolini Luca
2019

Abstract

Game theory has long served as a framework with which to model interactive decision making for scenarios where agents are motivated to maximize their individual welfare. However, when agents are influenced by the opinions and attitudes of others, the opportunity exists to make coordinated decisions in the pursuit of systematic group behavior. The application of conditional game theory, Bayesian network theory, and Markov convergence theory provides a framework within which to formalize a theory of coordinated decision making under social influence.
2019
Istituto di Scienze e Tecnologie della Cognizione - ISTC
Inglese
6th International Conference on Control, Decision and Information Technologies (CoDIT)
1161
1166
6
IEEE
New York
STATI UNITI D'AMERICA
Sì, ma tipo non specificato
23-26 April 2019
Paris, France, 2019
game theory
network theory
coordination
collaboration
1
none
Stirling, Wynn C.; Tummolini, Luca
273
info:eu-repo/semantics/conferenceObject
04 Contributo in convegno::04.01 Contributo in Atti di convegno
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/403844
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