2021
DOI: 10.1007/978-3-030-87473-5_22
|View full text |Cite
|
Sign up to set email alerts
|

A Dynamic Game Formulation for Control of Opinion Dynamics over Social Networks

Abstract: This paper considers the case where the opinion of agents in a social network is influenced not only by the other agents, but also by two marketers in competition. The main contributions of this work is to propose a dynamical game formulation of the problem and to conduct the corresponding equilibrium analysis. Due to the competition between the marketers, the opinions never reach consensus but are spread between the desired opinions of the two marketers. Our analysis provides practical insights to know how a … Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

0
11
0

Year Published

2024
2024
2024
2024

Publication Types

Select...
1

Relationship

0
1

Authors

Journals

citations
Cited by 1 publication
(11 citation statements)
references
References 10 publications
0
11
0
Order By: Relevance
“…where f : R n → R n is a function defined in accordance with the model that we wish to describe (details will appear below). Generalizing [15], [17], we now define opinion dynamics with affine control u ∈ R p as follows.…”
Section: A General Opinion Dynamics Modelmentioning
confidence: 99%
See 4 more Smart Citations
“…where f : R n → R n is a function defined in accordance with the model that we wish to describe (details will appear below). Generalizing [15], [17], we now define opinion dynamics with affine control u ∈ R p as follows.…”
Section: A General Opinion Dynamics Modelmentioning
confidence: 99%
“…Since the updated state from each player is incorporated into the optimization of the subsequent states, this defines a state feedback scheme, unlike the traditional optimal control approach, in which the optimal controls are computed over the entire time horizon. In fact, the state feedback proposed in [15] is computed from an infinite horizon model, iteratively using the Riccati equation. Similarly, in [17], the infinite horizon approach with discounting and the resulting feedback control from the Riccati equation is used.…”
Section: One Step Ahead Optimal Control (Osaoc)mentioning
confidence: 99%
See 3 more Smart Citations