Szczegóły publikacji
Opis bibliograficzny
Maps of tournaments: distances, experiments, and data / Filip Nikolow, Piotr FALISZEWSKI, Stanisław SZUFA // W: ECAI 2025 [Dokument elektroniczny] : 28th European Conference on Artificial Intelligence : 25–30 October 2025, Bologna, Italy : including 14th conference on Prestigious Applications of Intelligent Systems (PAIS 2025) : proceedings / ed. by Inês Lynce, [et al.]. — Wersja do Windows. — Dane tekstowe. — Amsterdam : IOS Press : Sage, cop. 2025. — ( Frontiers in Artificial Intelligence and Applications ; ISSN 0922-6389 ; vol. 413 ). — e-ISBN: 978-1-64368-631-8. — S. 675–682. — Wymagania systemowe: Adobe Reader. — Bibliogr. s. 682, Abstr. — S. Szufa - dod. afiliacja: CNRS, LAMSADE, Université Paris Dauphine – PSL, Paris, France
Autorzy (3)
Dane bibliometryczne
| ID BaDAP | 163998 |
|---|---|
| Data dodania do BaDAP | 2025-12-02 |
| Tekst źródłowy | URL |
| DOI | 10.3233/FAIA250866 |
| Rok publikacji | 2025 |
| Typ publikacji | materiały konferencyjne (aut.) |
| Otwarty dostęp |  |
| Creative Commons | |
| Wydawcy | IOS Press, SAGE Publications |
| Konferencja | European Conference on Artificial Intelligence 2025 |
| Czasopismo/seria | Frontiers in Artificial Intelligence and Applications |
Abstract
We form a “map of tournaments” by adapting the map framework from the world of elections. By a tournament we mean a complete directed graph where the nodes are the players and an edge points from a winner of a game to the loser (with no ties allowed). A map is a set of tournaments represented as points on a 2D plane, so that their Euclidean distances resemble the distances computed according to a given measure. We identify useful distance measures, discuss ways of generating random tournaments (and compare them to several real-life ones), and show how the maps are helpful in visualizing experimental results (also for knockout tournaments).
