Title
Consensus and Information Cascades in Game-Theoretic Imitation Dynamics with Static and Dynamic Network Topologies
Abstract
We construct a model of strategic imitation in an arbitrary network of players who interact through an additive game. Assuming a discrete time update, we show a condition under which the resulting difference equations converge to consensus. Two conjectures on general convergence are also discussed. We then consider the case where players not only may choose their strategies, but also affect their local topology. We show that for the prisoner's dilemma, the graph structure converges to a set of disconnected cliques and strategic consensus occurs in each clique. Several examples from various matrix games are provided. A variation of the model is then used to create a simple model for the spreading of trends, or information cascades in (e.g., social) networks. We provide theoretical and empirical results on the trend-spreading model.
Year
DOI
Venue
2019
10.1137/16M109675X
SIAM JOURNAL ON APPLIED DYNAMICAL SYSTEMS
Keywords
Field
DocType
consensus,convergence,imitation game,network,difference equation,cascade
Convergence (routing),Dynamic network analysis,Differential equation,Control theory,Information cascade,Network topology,Theoretical computer science,Cascade,Imitation,Discrete time and continuous time,Mathematics
Journal
Volume
Issue
ISSN
18
2
1536-0040
Citations 
PageRank 
References 
0
0.34
0
Authors
4
Name
Order
Citations
PageRank
Christopher Griffin15811.43
Sarah Michele Rajtmajer23110.06
Anna Cinzia Squicciarini31301106.30
Andrew Belmonte451.92