On learning algorithms for nash equilibria

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 6386 LNCS, Issue M4D, 2010, Pages 114-125

  Daskalakis, Constantinos ^a   Frongillo, Rafael ^b   Papadimitriou, Christos H ^b   Pierrakos, George ^b   Valiant, Gregory ^b  

^a MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPLEXITY ASSUMPTIONS; CONVERGENCE PROPERTIES; CUMULATIVE DISTRIBUTION; FICTITIOUS PLAY; IMPOSSIBILITY RESULTS; MULTIPLICATIVE UPDATES; NASH EQUILIBRIA; NASH EQUILIBRIUM; POTENTIAL FUNCTION; SIMPLE GAMES; SOLUTION CONCEPTS; ZERO-SUM GAME;

CONVERGENCE OF NUMERICAL METHODS; GAME THEORY; TELECOMMUNICATION NETWORKS;

LEARNING ALGORITHMS;

EID: 78649568164     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-16170-4_11     Document Type: Conference Paper

References (15)

1. Blum, A., Hajiaghayi, M., Ligett, K., Roth, A.: Regret minimization and price of total anarchy. In: STOC 2008(2008)
2. Friedman, E., Shenker, S.: Learning and implementation on the Internet. Working paper (1997)
3. Freund, Y., Schapire, R. E.: Adaptive game playing using multiplicative weights. Games and Economic Behavior 29, 79-103 (1999)
4. Hart, S., Mansour, Y.: The communication complexity of uncoupled Nash equilibrium procedures. In: STOC 2007(2007)
5. Hart, S., Mas-Colell, A.: A simple adaptive procedure leading to correlated equilibrium. Econometrica 68(5), 1127-1150 (2000)
6. Karlin, S.: Mathematical Methods and Theory in Games, Programming and Economics. Dover, New York (1994)
7. Kleinberg, R., Piliouras, G., Tardos, É.: Multiplicative updates outperform generic no-regret learning in congestion games. In: STOC 2009(2009)
8. Robinson, J.: An iterative method of solving a game. In: Annals of Mathematics (1951)
9. Roughgarden, T.: Intrinsic robustness of the price of anarchy. In: STOC 2009(2009)
10. Shapley, L. S.: Some topics in two-person games. In: Dresher, M., Aumann, R. J., Shapley, L. S., Tucker, A. W. (eds.) Advances in Ame Theory (1964)
11. Auer, P., Cesa-Bianchi, N., Freund, Y., Schapire, R. E.: The Nonstochastic Multiarmed Bandit Problem. SIAM J. Comput. 32(48), 77(2002)
12. Arora, S., Hazan, E., Kale, S.: The Multiplicative Weights Update Method: a Meta Algorithm and Applications (2005) (Manuscript)
13. Abernethy, J., Rakhlin, A.: Beating the adaptive bandit with high probability. In: COLT 2009(2009)
14. Zinkevich, M.: Theoretical guarantees for algorithms in multi-agent settings. Tech. Rep. CMU-CS-04-161, Carnegie Mellon University (2004)
15. Benaim, M., Hirsch, M. W.: Mixed Equilibria and Dynamical Systems Arising from Fictitious Play in Perturbed Games. Games and Economic Behavior 29, 36-72 (1999)