Ιδρυματικό Αποθετήριο
Πολυτεχνείο Κρήτης
Πολυτεχνείο Κρήτης
EN
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| URI: | http://purl.tuc.gr/dl/dias/833F3533-470E-451D-B850-1C380A396F74 | ||
| Έτος | 2020 | ||
| Τύπος | Πλήρης Δημοσίευση σε Συνέδριο | ||
| Άδεια Χρήσης |
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| 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. | ||
| Εμφανίζεται στις Συλλογές |
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. Usingthis 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 byusing optimised tactics from our Bayesian and stochastic games, we increase a team chances of winning by 16.1% and 3.4% respectively.
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