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National Repository of Grey Literature 2 records found  Search took 0.00 seconds. 
General Artificial Intelligence for Game Playing
 Klůj, Jan ; Pilát, Martin (advisor) ; Moudřík, Josef (referee)
Game playing is a relatively interesting task in the field of artificial intelligence in these days. The master thesis deals with general artificial intelligence which is capable of playing selected simple games based on information that is also avai- lable to the human player. Our selected games are 2048, Mario, racing simulator TORCS and Alhambra. All the information acquired by artificial intelligence is provided by games through an interface, therefore none of the models uses visual input. We use evolutionary approaches such as evolutionary algorithms, evolutio- nary strategy CMA and differential evolution applied to different types of neural networks. We are also dealing with deep reinforcement learning. We test these approaches and compare their results. 1
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Alhambra
 Klůj, Jan ; Holan, Tomáš (advisor) ; Mráz, František (referee)
Title: Alhambra Author: Jan Klůj Department: Department of Software and Computer Science Education Supervisor: RNDr. Tomáš Holan, Ph.D., Department of Software and Computer Science Education Abstract: The bachelor thesis deals with the implementation of the board game Alhambra. Besides of the implementation of the game rules, program includes also a graphical user interface. The game can be played by two to six players who take turns at one computer. Further we deal with an artificial intelligence, against which we can play. Decision logic of the artificial intelligence is made by using the evolution algorithm and machine learning. Keywords: Alhambra, game, artificial intelligence, evolution algorithm
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