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Werewolf is a popular party game throughout the world, and research on its significance has progressed in recent years.
Bagging predictors
Leo Breiman · 1996
Earlier work this paper cites.
Popular ensemble methods: An empirical study
David Opitz and Richard Maclin · 1999
Earlier work this paper cites.
Are you awerewolf? detecting deceptive roles and outcomes in a conversational role-playing game
Gokul Chittaranjan and Hayley Hung · 2010
Earlier work this paper cites.
The lemonade stand game competition: Solving unsolvable games
Martin Zinkevich, Michael Bowling, and Michael Wunder · 2011
Earlier work this paper cites.
Bagging, boosting and ensemble methods
Peter Bühlmann · 2012
Cited alongside, same era.
Movement design of a life-like agent for the werewolf game
Daisuke Katagami, Masashi Kanazawa, Fujio Toriumi, Hirotaka Osawa, Michimasa Inaba, and Kosuke Shinoda · 2015
Cited alongside, same era.
Werewolf game modeling using action probabilities based on play log analysis
Yuya Hirata, Michimasa Inaba, Kenichi Takahashi, Fujio Toriumi, Hirotaka Osawa, Daisuke Katagami, and Kousuke Shinoda · 2016
Cited alongside, same era.
Tracing werewolf game by using extended bdi model
Naoyuki Nide and Shiro TAKATA · 2017
Cited alongside, same era.
Ai wolf contest — development of game ai using collective intelligence —
Fujio Toriumi, Hirotaka Osawa, Michimasa Inaba, Daisuke Katagami, Kosuke Shinoda, and Hitoshi Matsubara · 2017
Later among the works it cites.
A general reinforcement learning algorithm that masters chess, shogi, and go through self-play
David Silver, Thomas Hubert, Julian Schrittwieser, Ioannis Antonoglou, Matthew Lai, Arthur Guez, Marc Lanctot, Laurent Sifre, Dharshan Kumaran, Thore Graepel, Timothy Lillicrap, Karen Simonyan, and Demis Hassabis · 2018
Later among the works it cites.
A weighted majority voting ensemble approach for classification
Alican Dogan and Derya Birant · 2019
Later among the works it cites.
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