Playing of Nondeterministic Games with Learning

The thesis is dedicated to the study and implementation of methods used for learning from the course of playing. The chosen game for this thesis is Backgammon. The algorithm used for training neural networks is called the temporal difference learning with use of eligible traces. This algorithm is also known as TD(lambda). The theoretical part describes algorithms for playing games without learning, introduction to reinforcement learning, temporal difference learning and introduction to artificial neural networks. The practical part deals with application of combination of neural networks and TD(lambda) algorithms