URI | http://purl.tuc.gr/dl/dias/833F3533-470E-451D-B850-1C380A396F74 | - |
Αναγνωριστικό | www.ifaamas.org/proceedings.html | - |
Αναγνωριστικό | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85096654096&partnerID=40&md5=ce843458300f4b248f93e6827a5ad262 | - |
Αναγνωριστικό | 978-145037518-4 | - |
Γλώσσα | en | - |
Μέγεθος | 9 pages | en |
Τίτλος | Optimising game tactics for football | en |
Δημιουργός | Beal Ryan | en |
Δημιουργός | Chalkiadakis Georgios | en |
Δημιουργός | Χαλκιαδακης Γεωργιος | el |
Δημιουργός | Norman Timothy J. | en |
Δημιουργός | Ramchurn Sarvapali D. | en |
Εκδότης | International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS) | en |
Περίληψη | In this paper we present a novel approach to optimise tactical and strategic decision making in football (soccer). We model the game of football as a multi-stage game which is made up from a Bayesian game to model the pre-match decisions and a stochastic game to model the in-match state transitions and decisions. Using
this formulation, we propose a method to predict the probability of game outcomes and the payoffs of team actions. Building upon this, we develop algorithms to optimise team formation and ingame tactics with different objectives. Empirical evaluation of our approach on real-world datasets from 760 matches shows that by
using optimised tactics from our Bayesian and stochastic games, we increase a team chances of winning by 16.1% and 3.4% respectively. | en |
Τύπος | Πλήρης Δημοσίευση σε Συνέδριο | el |
Τύπος | Conference Full Paper | en |
Άδεια Χρήσης | http://creativecommons.org/licenses/by/4.0/ | en |
Ημερομηνία | 2022-07-26 | - |
Ημερομηνία Δημοσίευσης | 2020 | - |
Θεματική Κατηγορία | Autonomous agents | en |
Θεματική Κατηγορία | Football | en |
Θεματική Κατηγορία | Game theory | en |
Θεματική Κατηγορία | Multi agent systems | en |
Θεματική Κατηγορία | Bayesian game | en |
Θεματική Κατηγορία | Stochastic game | en |
Βιβλιογραφική Αναφορά | R. Beal, G. Chalkiadakis, T. J. Norman, and S. D. Ramchurn, “Optimising game tactics for football,” In Proc. of the 19th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2020), vol 2020, B. An, N. Yorke-Smith, A. El Fallah Seghrouchni, G. Sukthankar, Eds., USA: IFAAMAS, 2020, pp. 141-149. | en |