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

Authors

602

  1. TS
    Tüomas Sandholm

    Carnegie Mellon University, United States

    12 publications · 553 citations

    12

    h-index

  2. CH
    Christos H. Papadimitriou

    University of California, Berkeley, United States

    9 publications · 843 citations

    9

    h-index

  3. CD
    Constantinos Daskalakis

    Massachusetts Institute of Technology, United States

    9 publications · 707 citations

    9

    h-index

  4. RJ
    Ramesh Johari

    Stanford University, United States

    8 publications · 237 citations

    8

    h-index

  5. GY
    Gabriel Y. Weintraub

    Stanford University, United States

    8 publications · 344 citations

    8

    h-index

1–5 of 602

Venues

  1. arXiv (Cornell University)

    Repository · 15 publications · 884 citations

    12

    h-index

  2. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 11 publications · 259 citations

    10

    h-index

  3. Journal of Economic Theory

    JET · 8 publications · 359 citations

    8

    h-index

  4. RePEc: Research Papers in Economics

    Repository · 8 publications · 165 citations

    8

    h-index

  5. Economic Theory

    7 publications · 197 citations

    7

    h-index

1–5