This paper reviews different applications of machine learning techniques in a development of AI player for a collectible card video game Hearthstone: Heroes of Warcraft. Its main objective is to present selected aspects of the game, in which machine learning can help an artificial player to make better decisions and increase its winning chances. Moreover, the paper describes some of experiments conducted by our research team at Silver Bullet Solutions, as a part of the research on GRAIL – a general framework for designing AI players in video games.
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How Machine Learning can improve AI in Hearthstone
Andrzej Janusz
Silver Bullet Labs
andrzej.janusz@silverbullet.pl
Author: Tomasz Tajmajer
Artificial intelligence methods are often perceived as extremely complicated and understandable only by people that graduated computer science. The idea of an electronic device that, by itself, learns how to behave still seems to be very futuristic. In fact, we have many “smart” devices around us, but many of them are not smarter than a motion-based light switch…
Read moreAuthor: Maciej Świechowski Ph.D.
“Look deep into nature, and then you will understand everything better” – Albert Einstein
Since ancient times, nature has been serving as inspiration for humans in the shaping of our civilization and culture. A plethora of brilliant inventions happened just through careful observation of nature…
Read moreAuthor: Andrzej Janusz
This paper reviews different applications of machine learning techniques in a development of AI player for a collectible card video game Hearthstone: Heroes of Warcraft.
Read moreAuthor: Piotr Beling
Decision making algorithm is an algorithm which tries to calculate the best move possible to make in a given position in a game. In other words, for given input position, it points the move which is possible the best one.
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