master's thesis
Domen Požrl (Author), Aleksander Sadikov (Mentor)

Abstract

In this thesis we study and analyse the effectiveness of Q-learning when it comes to learning and playing the card game Tarock. We present many problems that are inherently present in every attempt at mastering a card game with artificial intelligence. We developed several models, each with a distinct way of looking at the game and distinct behaviour in different game scenarios. We designed different testing conditions ranging from playing against theoretical players and other Tarock playing software, to playing against real people. We evaluated our models under real life and computational conditions. Our best performing model was able to compete with, and on many occasions beat an average Tarock player.

Keywords

reinforcement learning;Tarock;cards;game playing;computer science;computer and information science;master's thesis;

Data

Language: English
Year of publishing:
Typology: 2.09 - Master's Thesis
Organization: UL FRI - Faculty of Computer and Information Science
Publisher: [D. Požrl]
UDC: 004.8:794.4(043.2)
COBISS: 87302915 Link will open in a new window
Views: 187
Downloads: 40
Average score: 0 (0 votes)
Metadata: JSON JSON-RDF JSON-LD TURTLE N-TRIPLES XML RDFA MICRODATA DC-XML DC-RDF RDF

Other data

Secondary language: Slovenian
Secondary title: Spodbujevalno učenje v taroku
Secondary abstract: V tem magistrskem delu preučimo in analiziramo učinkovitost metode Q-learning v kontekstu učenja in igranja igre tarok. Predstavimo probleme, ki se pojavljajo pri vsakem poskusu igranja iger s kartami s pomočjo umetne inteligence. Razvili smo več modelov, vsakega z drugačnim pogledom na igro in drugačnim odgovorom na različna stanja igre. Zasnovali smo več testnih okolij, od igranja proti teoretičnim igralcem in drugim programom za igranje taroka, do igranja proti pravim ljudem. Modele smo ovrednotili pod življenjskimi in računskimi pogoji. Naš najboljši model se je uspešno boril in večkrat celo premagoval povprečne igralce taroka.
Secondary keywords: spodbujevalno učenje;tarok;karte;igranje iger;računalništvo in informatika;magisteriji;Tarok;Umetna inteligenca;Računalništvo;Univerzitetna in visokošolska dela;
Type (COBISS): Master's thesis/paper
Study programme: 1000471
Thesis comment: Univ. v Ljubljani, Fak. za računalništvo in informatiko
Pages: XVI, 82 str.
ID: 13870650