An algorithm for finding the nucleolus of assignment games
International Journal of Game Theory
The complexity of computing a Nash equilibrium
Proceedings of the thirty-eighth annual ACM symposium on Theory of computing
Settling the Complexity of Two-Player Nash Equilibrium
FOCS '06 Proceedings of the 47th Annual IEEE Symposium on Foundations of Computer Science
A Polynomial Time Algorithm for Computing an Arrow-Debreu Market Equilibrium for Linear Utilities
SIAM Journal on Computing
Balanced outcomes in social exchange networks
STOC '08 Proceedings of the fortieth annual ACM symposium on Theory of computing
Uncoordinated two-sided matching markets
Proceedings of the 9th ACM conference on Electronic commerce
Bargaining Solutions in a Social Network
WINE '08 Proceedings of the 4th International Workshop on Internet and Network Economics
Network bargaining: algorithms and structural results
Proceedings of the 10th ACM conference on Electronic commerce
Convergence of Local Dynamics to Balanced Outcomes in Exchange Networks
FOCS '09 Proceedings of the 2009 50th Annual IEEE Symposium on Foundations of Computer Science
A behavioral study of bargaining in social networks
Proceedings of the 11th ACM conference on Electronic commerce
Monotonicity in bargaining networks
SODA '10 Proceedings of the twenty-first annual ACM-SIAM symposium on Discrete Algorithms
An FPTAS for bargaining networks with unequal bargaining powers
WINE'10 Proceedings of the 6th international conference on Internet and network economics
Fast convergence of natural bargaining dynamics in exchange networks
Proceedings of the twenty-second annual ACM-SIAM symposium on Discrete Algorithms
Optimizing social welfare for network bargaining games in the face of unstability, greed and spite
ESA'12 Proceedings of the 20th Annual European conference on Algorithms
Bargaining for revenue shares on tree trading networks
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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We present a new technique for analyzing the rate of convergence of local dynamics in bargaining networks. The technique reduces balancing in a bargaining network to optimal play in a randomturn game. We analyze this game using techniques from martingale and Markov chain theory. We obtain a tight polynomial bound on the rate of convergence for a nontrivial class of unweighted graphs (the previous known bound was exponential). Additionally, we show this technique extends naturally to many other graphs and dynamics.