Theory of linear and integer programming
Theory of linear and integer programming
Fair distribution protocols or how the players replace fortune
Mathematics of Operations Research
The complexity of computing a Nash equilibrium
Proceedings of the thirty-eighth annual ACM symposium on Theory of computing
Proceedings of the twenty-fifth annual ACM symposium on Principles of distributed computing
Settling the Complexity of Two-Player Nash Equilibrium
FOCS '06 Proceedings of the 47th Annual IEEE Symposium on Foundations of Computer Science
STOC '08 Proceedings of the fortieth annual ACM symposium on Theory of computing
Equilibrium Points in Fear of Correlated Threats
WINE '08 Proceedings of the 4th International Workshop on Internet and Network Economics
Approximability and Parameterized Complexity of Minmax Values
WINE '08 Proceedings of the 4th International Workshop on Internet and Network Economics
A polynomial-time Nash equilibrium algorithm for repeated games
Decision Support Systems - Special issue: The fourth ACM conference on electronic commerce
Equilibrium Points in Fear of Correlated Threats
WINE '08 Proceedings of the 4th International Workshop on Internet and Network Economics
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The present work considers the following computational problem:Given any finite game in normal form G and the correspondinginfinitely repeated game G ∞ , determine inpolynomial time (wrt the representation of G) a profile ofstrategies for the players in G ∞ that is anequilibrium point wrt the limit-of-means payoff. The problem hasbeen solved for two players [10], based mainly on theimplementability of the threats for this case. Nevertheless, [4]demonstrated that the traditional notion of threats is acomputationally hard problem for games with at least 3 players (seealso [8]). Our results are the following: (i) We propose analternative notion of correlated threats, which is polynomial timecomputable (and therefore credible). Our correlated threats arealso more severe than the traditional notion of threats, but notoverwhelming for any individual player. (ii) When for theunderlying game G there is a correlated strategy with payoff vectorstrictly larger than the correlated threats vector, we efficientlycompute a polynomial–size (wrt the description of G)equilibrium point for G ∞ , for any constantnumber of players. (iii) Otherwise, we demonstrate the constructionof an equilibrium point for an arbitrary number of players and upto 2 concurrently positive payoff coordinates in any payoff vectorof G. This completely resolves the cases of 3 players, and providesa direction towards handling the cases of more than 3 players. Itis mentioned that our construction is not a Nash equilibrium point,because the correlated threats we use are implemented via, not onlyfull synchrony (as in [10]), but also coordination of the otherplayers’ actions. But this seems to be a fair trade-offbetween efficiency of the construction and players’coordination, in particular because it only affects the punishments(which are anticipated never to be used).