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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Evolutionary deckbuilding in hearthstone
Pablo García‐Sánchez, Alberto Tonda, Giovanni Squillero, et al.
(2016), pp. 1-8
Closed Access | Times Cited: 44

Showing 1-25 of 44 citing articles:

Mapping hearthstone deck spaces through MAP-elites with sliding boundaries
Matthew C. Fontaine, Scott Lee, L. B. Soros, et al.
Proceedings of the Genetic and Evolutionary Computation Conference (2019)
Open Access | Times Cited: 58
Improving Hearthstone AI by Combining MCTS and Supervised Learning Algorithms
Maciej Świechowski, Tomasz Tajmajer, Andrzej Janusz
(2018), pp. 1-8
Open Access | Times Cited: 49
Automated playtesting in collectible card games using evolutionary algorithms: A case study in hearthstone
Pablo García‐Sánchez, Alberto Tonda, Antonio M. Mora, et al.
Knowledge-Based Systems (2018) Vol. 153, pp. 133-146
Closed Access | Times Cited: 39
Monte Carlo tree search experiments in hearthstone
André Santos, Pedro A. Santos, Francisco S. Melo
(2017)
Closed Access | Times Cited: 37
Q-DeckRec: A Fast Deck Recommendation System for Collectible Card Games
Zhengxing Chen, Christopher Amato, Truong-Huy D. Nguyen, et al.
(2018), pp. 1-8
Open Access | Times Cited: 37
Exploring the hearthstone deck space
Aditya H. Bhatt, Scott Lee, Fernando de Mesentier Silva, et al.
(2018), pp. 1-10
Closed Access | Times Cited: 33
Optimizing Hearthstone agents using an evolutionary algorithm
Pablo García‐Sánchez, Alberto Tonda, Antonio J. Fernández, et al.
Knowledge-Based Systems (2019) Vol. 188, pp. 105032-105032
Open Access | Times Cited: 28
The Many AI Challenges of Hearthstone
Amy K. Hoover, Julian Togelius, Scott Lee, et al.
KI - Künstliche Intelligenz (2019) Vol. 34, Iss. 1, pp. 33-43
Closed Access | Times Cited: 26
Introducing Tales of Tribute AI Competition
Jakub Kowalski, Radosław Miernik, Katarzyna Polak-Kraśna, et al.
2021 IEEE Conference on Games (CoG) (2024), pp. 1-8
Open Access | Times Cited: 2
Helping AI to Play Hearthstone: AAIA’17 Data Mining Challenge
Andrzej Janusz, Tomasz Tajmajer, Maciej Świechowski
Annals of Computer Science and Information Systems (2017)
Open Access | Times Cited: 25
Evolving the Hearthstone Meta
Fernando de Mesentier Silva, Rodrigo Canaan, Scott Lee, et al.
2021 IEEE Conference on Games (CoG) (2019), pp. 1-8
Open Access | Times Cited: 23
Summarizing Strategy Card Game AI Competition
Jakub Kowalski, Radosław Miernik
2021 IEEE Conference on Games (CoG) (2023), pp. 1-8
Open Access | Times Cited: 5
Toward an Intelligent HS Deck Advisor: Lessons Learned from AAIA'18 Data Mining Competition
Andrzej Janusz, Tomasz Tajmajer, Maciej Świechowski, et al.
Annals of Computer Science and Information Systems (2018) Vol. 15, pp. 189-192
Open Access | Times Cited: 16
Evolutionary Approach to Collectible Arena Deckbuilding using Active Card Game Genes
Jakub Kowalski, Radosław Miernik
2022 IEEE Congress on Evolutionary Computation (CEC) (2020), pp. 1-8
Closed Access | Times Cited: 14
Learning multimodal entity representations and their ensembles, with applications in a data-driven advisory framework for video game players
Andrzej Janusz, Daniel Kałuża, Maciej Matraszek, et al.
Information Sciences (2022) Vol. 617, pp. 193-210
Closed Access | Times Cited: 7
Improving Hearthstone AI by Combining MCTS and Supervised Learning Algorithms
Maciej Świechowski, Tomasz Tajmajer, Andrzej Janusz
arXiv (Cornell University) (2018)
Closed Access | Times Cited: 11
Evolutionary Approach to Collectible Card Game Arena Deckbuilding using Active Genes
Jakub Kowalski, Radosław Miernik
arXiv (Cornell University) (2020)
Open Access | Times Cited: 9
Predicting Human Card Selection in Magic: The Gathering with Contextual Preference Ranking
Timo Bertram, Johannes Fürnkranz, Martin Müller
2021 IEEE Conference on Games (CoG) (2021), pp. 1-8
Open Access | Times Cited: 9
Evolving Evaluation Functions for Collectible Card Game AI
Radosław Miernik, Jakub Kowalski
Proceedings of the 14th International Conference on Agents and Artificial Intelligence (2022)
Open Access | Times Cited: 6
SENSEI: An Intelligent Advisory System for the eSport Community and Casual Players
Andrzej Janusz, Dominik Ślęzak, Sebastian Stawicki, et al.
IEEE/WIC/ACM International Conference on Web Intelligence (WI'04) (2018), pp. 754-757
Closed Access | Times Cited: 9
AI solutions for drafting in Magic: the Gathering
Henry N. Ward, Bobby Mills, Daniel J. Brooks, et al.
2021 IEEE Conference on Games (CoG) (2021), pp. 1-8
Open Access | Times Cited: 8
Automated Team Assembly in Mobile Games: A Data-Driven Evolutionary Approach Using a Deep Learning Surrogate
Yue‐Jiao Gong, Jianxiong Guo, Da-Lue Lin, et al.
IEEE Transactions on Games (2022) Vol. 15, Iss. 1, pp. 67-80
Closed Access | Times Cited: 5
CreativeStone: A Creativity Booster for Hearthstone Card Decks
Celso França, Zisen Zhou, Carolina Fernanda da Silva, et al.
IEEE Transactions on Games (2023) Vol. 16, Iss. 1, pp. 214-224
Closed Access | Times Cited: 2
Evolving the Hearthstone Meta
Fernando de Mesentier Silva, Rodrigo Canaan, Scott Lee, et al.
arXiv (Cornell University) (2019)
Closed Access | Times Cited: 6
Helping AI to Play Hearthstone: AAIA'17 Data Mining Challenge
Andrzej Janusz, Maciej Świechowski, Tomasz Tajmajer
arXiv (Cornell University) (2017)
Closed Access | Times Cited: 5
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