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
Parents
21
Ralph Gasser · Computational Intelligence · 1996 · 68 citations
The Open International Soccer Database for machine learning
Werner Dubitzky, Philippe Lopes, Jesse Davis et al. · Machine Learning · 2018 · 58 citations · Full text
Karen Thompson · ICGA Journal · 1996 · 51 citations
1–5 of 21
42
3
h-index
3
h-index
2
h-index
Institute of Information Science, Academia Sinica, Taiwan
2 publications · 37 citations
2
h-index
Rutgers, The State University of New Jersey, United States
2 publications · 59 citations
2
h-index
1–5 of 42
18
Maastricht University
Maastricht, The Netherlands
2 h-index
7 publications
116 citations

University of Alberta
Edmonton, Canada
2 h-index
3 publications
39 citations

Northeastern University
Shenyang, China
1 h-index
1 publications
35 citations
Palo Alto Institute
San Mateo, United States
1 h-index
1 publications
13 citations

Helmholtz Zentrum München
Munich, Germany
1 h-index
1 publications
58 citations
Université Paris Cité
Paris, France
1 h-index
1 publications
58 citations

Université d'Évry Val-d'Essonne
Évry-Courcouronnes, France
1 h-index
1 publications
58 citations

Vrije Universiteit Amsterdam
Amsterdam, The Netherlands
1 h-index
2 publications
46 citations
1–8 of 18
8 publications · 170 citations
8
h-index
2 publications · 31 citations
2
h-index
1 publications · 18 citations
1
h-index
1 publications · 13 citations
1
h-index
1 publications · 58 citations
1
h-index
1–5