Thesis Details
Neuronové sítě pro hru gomoku
The goal of this thesis is to create an artificial intelligence for playing Gomoku. While conventional methods usually use state space search combined with predefined rules, this artificial intelligence uses state space search and learned neural networks. A strategic network computes probability distribution for given a board state and a value network determines outcome of the game from a given board state. I trained multiple architectures of neural networks with different number of convolutional layers and different sizes of convolution kernels. Experiments show, that it is problematic to end a game without using the value network or search algorithm, but the strategic network can be used as a heuristic for choosing next move. Despite using relatively small dataset, created artificial intelligence is capable of beating weaker programs from Gomocup competition.
Artificial intelligence, Neural networks, Gomoku
Češka Milan, doc. RNDr., Ph.D. (DITS FIT BUT), člen
Martínek Tomáš, doc. Ing., Ph.D. (DCSY FIT BUT), člen
Ryšavý Ondřej, doc. Ing., Ph.D. (DIFS FIT BUT), člen
Španěl Michal, Ing., Ph.D. (DCGM FIT BUT), člen
@bachelorsthesis{FITBT20168, author = "Mat\'{u}\v{s} Bako", type = "Bachelor's thesis", title = "Neuronov\'{e} s\'{i}t\v{e} pro hru gomoku", school = "Brno University of Technology, Faculty of Information Technology", year = 2017, location = "Brno, CZ", language = "czech", url = "https://www.fit.vut.cz/study/thesis/20168/" }