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ICML
1998
IEEE
16 years 3 days ago
Multiagent Reinforcement Learning: Theoretical Framework and an Algorithm
In this paper, we adopt general-sum stochastic games as a framework for multiagent reinforcement learning. Our work extends previous work by Littman on zero-sum stochastic games t...
Junling Hu, Michael P. Wellman
STOC
2006
ACM
132views Algorithms» more  STOC 2006»
15 years 11 months ago
Near-optimal algorithms for unique games
Unique games are constraint satisfaction problems that can be viewed as a generalization of Max-Cut to a larger domain size. The Unique Games Conjecture states that it is hard to ...
Moses Charikar, Konstantin Makarychev, Yury Makary...
ISPDC
2008
IEEE
15 years 5 months ago
Computing Equilibria in Bimatrix Games by Parallel Support Enumeration
We consider the problem of computing all Nash equilibria in bimatrix games (i.e., nonzero-sum two-player noncooperative games). Computing all Nash equilibria for large bimatrix ga...
Jonathan Widger, Daniel Grosu
SAGT
2010
Springer
175views Game Theory» more  SAGT 2010»
14 years 9 months ago
On Learning Algorithms for Nash Equilibria
Can learning algorithms find a Nash equilibrium? This is a natural question for several reasons. Learning algorithms resemble the behavior of players in many naturally arising gam...
Constantinos Daskalakis, Rafael Frongillo, Christo...
ICML
2004
IEEE
16 years 3 days ago
Sequential skewing: an improved skewing algorithm
This paper extends previous work on the Skewing algorithm, a promising approach that allows greedy decision tree induction algorithms to handle problematic functions such as parit...
Soumya Ray, David Page