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Few new hearthstone and hanabi papers

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@ -192,6 +192,7 @@ If you aren't able to access any paper on this list, please [try using Sci-Hub](
- [Analysis of Symmetry and Conventions in Off-Belief Learning (OBL) in Hanabi](https://fanpu.io/blog/2022/symmetry-and-conventions-in-obl-hanabi/) (blogPost)
- [Using intuitive behavior models to adapt to and work with human teammates in Hanabi](http://reports-archive.adm.cs.cmu.edu/anon/anon/usr0/ftp/usr/ftp/2022/abstracts/22-119.html) (thesis)
- [Behavioral Differences is the Key of Ad-hoc Team Cooperation in Multiplayer Games Hanabi](http://arxiv.org/abs/2303.06775) (preprint)
- [The Hidden Rules of Hanabi: How Humans Outperform AI Agents](https://dl.acm.org/doi/10.1145/3544548.3581550) (conferencePaper)
# Hearthstone
- [Mapping Hearthstone Deck Spaces through MAP-Elites with Sliding Boundaries](http://arxiv.org/abs/1904.10656) (journalArticle)
@ -206,6 +207,9 @@ If you aren't able to access any paper on this list, please [try using Sci-Hub](
- [Optimizing Hearthstone agents using an evolutionary algorithm](https://linkinghub.elsevier.com/retrieve/pii/S0950705119304356) (journalArticle)
- [Exploring the hearthstone deck space](https://dl.acm.org/doi/10.1145/3235765.3235791) (conferencePaper)
- [Computational Intelligence Techniques for Games with Incomplete Information](https://webthesis.biblio.polito.it/26844/) (thesis)
- [Perfect Information Hearthstone is PSPACE-hard](http://arxiv.org/abs/2305.12731) (preprint)
- [Summarizing Strategy Card Game AI Competition](http://arxiv.org/abs/2305.11814) (preprint)
- [Towards sample efficient deep reinforcement learning in collectible card games](https://linkinghub.elsevier.com/retrieve/pii/S1875952123000496) (journalArticle)
# Hive
- [On the complexity of Hive](https://dspace.library.uu.nl/handle/1874/396955) (thesis)

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@ -11629,6 +11629,232 @@ the top-performing agents in previous competitions and outperformed most of them
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