On the Inefficiency Ratio of Stable Equilibria in Congestion Games
WINE '09 Proceedings of the 5th International Workshop on Internet and Network Economics
Dynamics in network interaction games
DISC'09 Proceedings of the 23rd international conference on Distributed computing
Mixing time and stationary expected social welfare of logit dynamics
SAGT'10 Proceedings of the Third international conference on Algorithmic game theory
Convergence to equilibrium of logit dynamics for strategic games
Proceedings of the twenty-third annual ACM symposium on Parallelism in algorithms and architectures
Optimal gateway selection in multi-domain wireless networks: a potential game perspective
MobiCom '11 Proceedings of the 17th annual international conference on Mobile computing and networking
Metastability of logit dynamics for coordination games
Proceedings of the twenty-third annual ACM-SIAM symposium on Discrete Algorithms
Stable sets of threshold-based cascades on the erdős-rényi random graphs
IWOCA'11 Proceedings of the 22nd international conference on Combinatorial Algorithms
An analysis of one-dimensional schelling segregation
STOC '12 Proceedings of the forty-fourth annual ACM symposium on Theory of computing
Triggering cascades on undirected connected graphs
Information Processing Letters
Hypergraph coloring games and voter models
WAW'12 Proceedings of the 9th international conference on Algorithms and Models for the Web Graph
Reversible iterative graph processes
Theoretical Computer Science
Decentralized dynamics for finite opinion games
SAGT'12 Proceedings of the 5th international conference on Algorithmic Game Theory
Diffusion dynamics of network technologies with bounded rational users: aspiration-based learning
IEEE/ACM Transactions on Networking (TON)
Logit dynamics: a model for bounded rationality
ACM SIGecom Exchanges
| Hi-index | 0.00 |
We study a simple game theoretic model for the spread of an innovation in a network. The diffusion of the innovation is modeled as the dynamics of a coordination game in which the adoption of a common strategy between players has a higher payoff. Classical results in game theory provide a simple condition for an innovation to become widespread in the network. The present paper characterizes the rate of convergence as a function of graph structure. In particular, we derive a dichotomy between well-connected (e.g. random) graphs that show slow convergence and poorly connected, low dimensional graphs that show fast convergence.