Approximation Algorithms For Equilibria
Approximation Algorithms for Equilibria is a computational framework in algorithmic game theory that systematically designs efficient algorithms to compute near-optimal solutions for equilibrium concepts when exact computation is intractable.
367
Publications
19K
Citations
602
Authors
316
Institutions
Publications per year
2017–2026
67
Parents
367
Equilibrium programming in Hilbert spaces
Patrick L. Combettes, Sever A. Hirstoaga · 2014 · 929 citations
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
1–5 of 367
602
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University of California, Berkeley, United States
9 publications · 843 citations
9
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Massachusetts Institute of Technology, United States
9 publications · 707 citations
9
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8
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8
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1–5 of 602
316
Carnegie Mellon University
Pittsburgh, United States
18 h-index
39 publications
1.6K citations
University of California, Berkeley
Berkeley, United States
16 h-index
29 publications
2K citations
Stanford University
Stanford, United States
14 h-index
40 publications
1.7K citations
University of Michigan
Ann Arbor, United States
11 h-index
22 publications
1.1K citations
Massachusetts Institute of Technology
Cambridge, United States
11 h-index
15 publications
745 citations
Microsoft (United States)
Redmond, United States
11 h-index
13 publications
1.1K citations
University of Illinois Urbana-Champaign
Urbana, United States
10 h-index
13 publications
273 citations
University of Pennsylvania
Philadelphia, United States
10 h-index
13 publications
1.7K citations
1–8 of 316
Repository · 15 publications · 884 citations
12
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Conference · 11 publications · 259 citations
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JET · 8 publications · 359 citations
8
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Repository · 8 publications · 165 citations
8
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7 publications · 197 citations
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