Hearthstone AI Competition
The collectible online card game Hearthstone features a rich testbed and poses unique demands for generating artificial intelligence agents. The game is a turn-based card game between two opponents, using constructed decks of thirty cards along with a selected hero with a unique power. Players use their limited mana crystals to cast spells or summon minions to attack their opponent, with the goal to reduce the opponent’s health to zero. The competition aims to promote the stepwise development of fully autonomous AI agents in the context of Hearthstone.
Entrants will submit agents to participate in one of the two tracks:
- Premade Deck Playing”-track: participants will receive a list of three known decks and three decks unknown prior submission. During evaluation we will simulate all possible matchups for at least 100 games to determine the average win-rate for each agent. Determining and using the characteristics of the player’s and the opponent’s deck to the player’s advantage will help in winning the game. The decks for the premade deck playing track can be found under:
- Three more meta-decks will be used, but will remain unknown to the participants till the final submission deadline.
- “User Created Deck Playing”-track: the competition framework allows agents to define their own deck. Finding a deck that can consistently beat a vast amount of other decks will play a key role in this competition track. Additionally, it gives the participants the chance in optimizing the agents’ strategy to the characteristics of their chosen deck.
Competition Entry Deadline: July15th 2019 23:59 UTC-12
In case you submit a paper based on this framework we would be happy if you could include the following citation:
Dockhorn, A., & Mostaghim, S. (2019). Introducing the Hearthstone-AI Competition, (Section IV), 1–4. Retrieved from http://arxiv.org/abs/1906.04238
The Hearthstone-AI Competition is being organised by:
- Alexander Dockhorn, Otto-von-Guericke University of Magdeburg
- Sanaz Mostaghim, Otto-von-Guericke University of Magdeburg
We would like to thank the developers of the Sabberstone Framework on which our competition is based on. Special thanks go out to darkfriend77 who is the current organizer of the Sabberstone github.