Approximate Nash Equilibrium
An Approximate Nash Equilibrium is a strategy profile in which no player can achieve a significantly improved payoff by unilaterally deviating, satisfying an ε-tolerance criterion relative to a true Nash Equilibrium within a non-cooperative game.
224
Publications
11.7K
Citations
385
Authors
206
Institutions
Publications per year
2017–2026
67
Variants
ε-Nash Equilibrium
Parents
224
Graphical Models for Game Theory
Michael Kearns, Michael L. Littman, Satinder Singh · arXiv (Cornell University) · 2013 · 574 citations · Full text
Playing large games using simple strategies
Richard J. Lipton, Evangelos Markakis, Aranyak Mehta · 2003 · 398 citations
Generalization and Equilibrium in Generative Adversarial Nets (GANs)
Sanjeev Arora, Rong Ge, Yingyu Liang et al. · arXiv (Cornell University) · 2017 · 211 citations · Full text
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Massachusetts Institute of Technology, United States
7 publications · 610 citations
7
h-index
1–5 of 385
206
University of California, Berkeley
Berkeley, United States
15 h-index
28 publications
1.7K citations
Carnegie Mellon University
Pittsburgh, United States
12 h-index
25 publications
1.4K citations
University of Pennsylvania
Philadelphia, United States
10 h-index
15 publications
835 citations
University of Patras
Pátrai, Greece
9 h-index
9 publications
335 citations

University of Liverpool
Liverpool, United Kingdom
8 h-index
23 publications
671 citations
Princeton University
Princeton, United States
8 h-index
16 publications
1.5K citations
University of Michigan
Ann Arbor, United States
7 h-index
16 publications
410 citations
Columbia University
New York, United States
7 h-index
9 publications
325 citations
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Repository · 24 publications · 1.4K citations
14
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Conference · 8 publications · 159 citations
8
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7 publications · 493 citations
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7 publications · 347 citations
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5 publications · 203 citations
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