Reinforcement learning in TarockPožrl, Domen (Avtor) Sadikov, Aleksander (Mentor) reinforcement learningTarockcardsgame playingIn 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.20212021-11-10 14:10:00Magistrsko delo/naloga133070VisID: 29121COBISS_ID: 87302915sl