Contact us

AAIA’17 Data Mining Challenge Concluded

On 23rd March 2017 our competition AAIA’17 Data Mining Challenge: Helping AI to Play Hearthstone started, and it finished on 28th June 2017 with the final deadline for submissions of papers selected for presentation at the conference.  By the end of competition there were 296 teams from 28 countries registered in the challenge. Among them, 188 teams submitted at least one solution to the public leaderboard and 114 teams described their solution in a report uploaded to the Knowledge Pit platform.

All top-ranked teams used neural networks in their solutions and the winners focused only on the convolutional neural networks. Another popular approach was the utilization of xgboost algorithm. There were also much simpler approaches which turned to be efficient, such as the logistic regression models. Moreover, all of these methods were often combined – techniques such as averaging, bagging or stacking were commonly used to obtain better prediction results.

Our own paper summarizing the competition results „Helping AI to Play Hearthstone: AAIA’17 Data Mining Challenge” passed the review stage and is ready for the publication as a part of the conference’s proceedings.

It was the most popular competition among challenges organized at Knowledge Pit to this day. Thanks to all of you who participated!

You might also like

AAIA’17 Data Mining Challenge Concluded

AAIA’17 Data Mining Challenge is the fourth data mining competition organized within the framework of International Symposium Advances in Artificial Intelligence and Applications. This time, the task is to come up with an efficient prediction model which would help AI to play the game of Hearthstone: Heroes of Warcraft. The competition is kindly sponsored by Silver Bullet Solutions and Polish Information Processing Society (PTI).

Read more
How Machine Learning can improve AI in Hearthstone: Heroes of Warcraft

Author: 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 more
Could you train your vacuum cleaner like your dog?

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 more
Next challenge for AI after winning with top human chess, go and poker players

In chess and go games all information needed for AI analysis is literally on the table. According to game experts winning in no-limit poker shows that AI is ready to win in cybersecurity, negotiations, military, auctions and even in containing infections.

Read more