Random early detection gateways for congestion avoidance
IEEE/ACM Transactions on Networking (TON)
A randomized online algorithm for bandwidth utilization
SODA '02 Proceedings of the thirteenth annual ACM-SIAM symposium on Discrete algorithms
Potential-Based Algorithms in On-Line Prediction and Game Theory
Machine Learning
Optimization problems in congestion control
FOCS '00 Proceedings of the 41st Annual Symposium on Foundations of Computer Science
Convex Optimization
Efficiency Loss in a Network Resource Allocation Game
Mathematics of Operations Research
Proceedings of the twenty-fifth annual ACM symposium on Principles of distributed computing
The communication complexity of uncoupled nash equilibrium procedures
Proceedings of the thirty-ninth annual ACM symposium on Theory of computing
Logarithmic regret algorithms for online convex optimization
Machine Learning
From External to Internal Regret
The Journal of Machine Learning Research
Regret minimization and the price of total anarchy
STOC '08 Proceedings of the fortieth annual ACM symposium on Theory of computing
Exploiting concavity in bimatrix games: new polynomially tractable subclasses
APPROX/RANDOM'10 Proceedings of the 13th international conference on Approximation, and 14 the International conference on Randomization, and combinatorial optimization: algorithms and techniques
No regret learning in oligopolies: cournot vs. bertrand
SAGT'10 Proceedings of the Third international conference on Algorithmic game theory
Coalition formation and price of anarchy in cournot oligopolies
WINE'10 Proceedings of the 6th international conference on Internet and network economics
Beyond myopic best response (in Cournot competition)
Proceedings of the twenty-third annual ACM-SIAM symposium on Discrete Algorithms
Quasi-proportional mechanisms: prior-free revenue maximization
LATIN'10 Proceedings of the 9th Latin American conference on Theoretical Informatics
On mutual concavity and strategically-zero-sum bimatrix games
Theoretical Computer Science
A dynamic axiomatic approach to first-price auctions
Proceedings of the fourteenth ACM conference on Electronic commerce
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We study a general sub-class of concave games which we call socially concave games. We show that if each player follows any no-external regret minimization procedure then the dynamics will converge in the sense that both the average action vector will converge to a Nash equilibrium and that the utility of each player will converge to her utility in that Nash equilibrium. We show that many natural games are indeed socially concave games. Specifically, we show that linear Cournot competition and linear resource allocation games are socially-concave games, and therefore our convergence result applies to them. In addition, we show that a simple best response dynamics might diverge for linear resource allocation games, and is known to diverge for linear Cournot competition. For the TCP congestion games we show that "near" the equilibrium the games are socially-concave, and using our general methodology we show the convergence of a specific regret minimization dynamics.