Hearthstone AI Competition

Organisers

Alexander Dockhorn, Queen Mary University of London, UK, a.dockhorn@qmul.ac.uk

Sanaz Mostaghim, University of Magdeburg, Germany, sanaz.mostaghim@ovgu.de

Contact

a.dockhorn@qmul.ac.uk

Description

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.

During the game, both players need to play the best combination of hand cards, while facing a large amount of uncertainty. The upcoming card draw, the opponent’s hand cards, as well as some hidden effects played by the opponent can influence the player’s next move and its succeeding rounds. Predicting the opponent’s deck from previously seen cards, and estimating the chances of getting cards of the own deck can help in finding the best cards to be played. Card playing order, their effects, as well as attack targets have a large influence on the player’s chances of winning the game.

Despite using premade decks players face the opportunity of creating a deck of 30 cards from the over 1000 available in the current game. Most of them providing unique effects and card synergies that can help in developing combos. Generating a strong deck is a step in consistently winning against a diverse set of opponents.

Tracks

The competition will encourage submissions to the following two separate tracks, which will be available in the second year of this competition:

In the “Premade Deck Playing”-track participants will receive a list of decks and play out all combinations against each other. Determining and using the characteristics of player’s and the opponent’s deck to the player’s advantage will help in winning the game. This track will feature an updated list of decks to better represent the current meta-game.

The “User Created Deck Playing”-track invites all participants in creating their own decks or choosing from the vast amount of decks available online. Finding a deck that can consistently beat multiple 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 Website

You can find more information on this year’s competition and the evaluation of last year’s submissions on our webpage. It also features a list of previously submitted bots and their source code as well as information about how to get started.

https://www.is.ovgu.de/Research/HearthstoneAI.html

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