|
|
Machine Learning in Strategic Games
Vlček, Michael ; Škoda, Petr (referee) ; Smrž, Pavel (advisor)
Machine learning is spearheading progress for the field of artificial intelligence in terms of providing competition in strategy games to a human opponent, be it in a game of chess, Go or poker. A field of machine learning, which shows the most promising results in playing strategy games, is reinforcement learning. The next milestone for the current research lies in a computer game Starcraft II, which outgrows the previous ones in terms of complexity, and represents a potential new breakthrough in this field. The paper focuses on analysis of the problem, and suggests a solution incorporating a reinforcement learning algorithm A2C and hyperparameter optimization implementation PBT, which could mean a step forward for the current progress.
|
|
|
Prediction of Raining from Meteoradar
Vlček, Michael ; Pešán, Jan (referee) ; Szőke, Igor (advisor)
This thesis deals with rain prediction using information from meteoradar images and some other relevant factors through the computational model of a neural network. It focuses on exploring different prediction possibilities using this model and defining the most successful model configuration to fulfill the chosen task.
|
|
|
Machine Learning in Strategic Games
Vlček, Michael ; Škoda, Petr (referee) ; Smrž, Pavel (advisor)
Machine learning is spearheading progress for the field of artificial intelligence in terms of providing competition in strategy games to a human opponent, be it in a game of chess, Go or poker. A field of machine learning, which shows the most promising results in playing strategy games, is reinforcement learning. The next milestone for the current research lies in a computer game Starcraft II, which outgrows the previous ones in terms of complexity, and represents a potential new breakthrough in this field. The paper focuses on analysis of the problem, and suggests a solution incorporating a reinforcement learning algorithm A2C and hyperparameter optimization implementation PBT, which could mean a step forward for the current progress.
|
|
|
Prediction of Raining from Meteoradar
Vlček, Michael ; Pešán, Jan (referee) ; Szőke, Igor (advisor)
This thesis deals with rain prediction using information from meteoradar images and some other relevant factors through the computational model of a neural network. It focuses on exploring different prediction possibilities using this model and defining the most successful model configuration to fulfill the chosen task.
|
guest ::
RSS feed.