Projects per year
In this paper, we introduce a Monte-Carlo tree search (MCTS) approach for the game “Hearthstone: Heroes of Warcraft”. We argue that, in light of the challenges posed by the game (such as uncertainty and hidden information), Monte Carlo tree search offers an appealing alternative to existing AI players. Additionally, by enriching MCTS with a properly constructed heuristic, it is possible to introduce significant gains in performance.We illustrate through extensive empirical validation the superior performance of our approach against vanilla MCTS and the current state-of-the art AI for Hearthstone.
|Title of host publication||2017 IEEE Conference on Computational Intelligence and Games (CIG)|
|Place of Publication||New York, NY|
|Publication status||Published - 2017|
|Event||2017 Conference on Computational Intelligence in Games - New York University, New York, United States|
Duration: 22 Aug 2017 → 25 Aug 2017
|Conference||2017 Conference on Computational Intelligence in Games|
|Period||22/08/17 → 25/08/17|
- Monte Carlo Tree Search
- Artificial intelligence for games
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Rage: Realising an Applied Gaming Eco-system
Westera, W., Georgiadis, K., Saveski, G., van Lankveld, G., Bahreini, K., van der Vegt, W., Berkhout, J., Nyamsuren, E., Kluijfhout, E. & Nadolski, R.
1/02/15 → 31/07/19