Endgame Databases

Endgame Databases is a computational framework that systematically encodes all possible positions and optimal outcomes for endgame scenarios in two-player perfect-information games, enabling exhaustive backward induction from terminal positions to determine theoretically optimal moves.

21

Publications

540

Citations

42

Authors

18

Institutions

Publications per year

2017–2026

1

Authors

42

  1. JS
    Jonathan Schaeffer

    University of Alberta, Canada

    3 publications · 77 citations

    3

    h-index

  2. PL
    Paul Lu

    University of Alberta, Canada

    3 publications · 77 citations

    3

    h-index

  3. DS
    Duane Szafron

    University of Alberta, Canada

    2 publications · 33 citations

    2

    h-index

  4. TH
    Tsan‐sheng Hsu

    Institute of Information Science, Academia Sinica, Taiwan

    2 publications · 37 citations

    2

    h-index

  5. RW
    Robert W. Lake

    Rutgers, The State University of New Jersey, United States

    2 publications · 59 citations

    2

    h-index

1–5 of 42

Venues

  1. ICGA Journal

    8 publications · 170 citations

    8

    h-index

  2. 2

    h-index

  3. New Mathematics and Natural Computation

    1 publications · 18 citations

    1

    h-index

  4. Theoretical Computer Science

    1 publications · 13 citations

    1

    h-index

  5. Machine Learning

    1 publications · 58 citations

    1

    h-index

1–5