Chess and Go, finding prior work on more contemporary games can be a bit hard. This list focuses on the latter. If you are interested in well-researched
games like Chess, Go, Hex, take a look at the [Chess programming wiki](https://www.chessprogramming.org/Games) instead.
- [The Hanabi challenge: A new frontier for AI research](https://doi.org/10.1016/j.artint.2019.103216) [[arXiv](https://arxiv.org/abs/1902.00506)]] (DeepMind)
- [Solving Hanabi: Estimating Hands by Opponent's Actions in Cooperative Game with Incomplete Information](https://www.aaai.org/ocs/index.php/WS/AAAIW15/paper/view/10167/10193)
- [A Browser-based Interface for the Exploration and Evaluation of Hanabi AIs](http://fdg2017.org/papers/FDG2017_demo_Hanabi.pdf)
- [I see what you see: Integrating eye tracking into Hanabi playing agents](http://www.exag.org/wp-content/uploads/2018/10/AIIDE-18_Upload_112.pdf)
- [Evaluating the Rainbow DQN Agent in Hanabi with Unseen Partners](https://arxiv.org/abs/2004.13291)
# Monopoly
- [Negotiation strategy of agents in the MONOPOLY game](https://ieeexplore.ieee.org/abstract/document/1013210)
- [Generating interesting Monopoly boards from open data](https://ieeexplore.ieee.org/abstract/document/6374168)
- [Estimating the probability that the game of Monopoly never ends](https://ieeexplore.ieee.org/abstract/document/5429349)
- [Learning to play Monopoly:A Reinforcement Learning approach](https://www.researchgate.net/profile/Anestis_Fachantidis/publication/289403522_Learning_to_play_monopoly_A_Reinforcement_learning_approach/links/59dd1f3e458515f6efef1904/Learning-to-play-monopoly-A-Reinforcement-learning-approach.pdf)
- [Monopoly as a Markov Process](https://doi.org/10.1080/0025570X.1972.11976187)
- [Learning to Play Monopoly withMonte Carlo Tree Search](https://project-archive.inf.ed.ac.uk/ug4/20181042/ug4_proj.pdf)
- [Monopoly Using Reinforcement Learning ](https://ieeexplore.ieee.org/abstract/document/8929523)
- [A Markovian Exploration of Monopoly](https://pi4.math.illinois.edu/wp-content/uploads/2014/10/Gartland-Burson-Ferguson-Markovopoly.pdf)
- [What's the best Monopoly strategy](https://publications.lakeforest.edu/cgi/viewcontent.cgi?referer=&httpsredir=1&article=1277&context=gss)
# Magic: the Gathering
- [Magic: the Gathering is as Hard as Arithmetic](https://arxiv.org/abs/2003.05119)
- [Magic: The Gathering is Turing Complete](https://arxiv.org/abs/1904.09828)
- [Neural Networks Models for Analyzing Magic: the Gathering Cards](https://arxiv.org/abs/1810.03744)
- [Ensemble Determinization in Monte Carlo Tree Search for the Imperfect Information Card Game Magic: The Gathering](https://doi.org/10.1109/TCIAIG.2012.2204883)
- [Deckbuilding in Magic: The Gathering Using a Genetic Algorithm](http://hdl.handle.net/11250/2462429)
# Terra Mystica
- [Using Tabu Search Algorithm for Map Generation in the Terra Mystica Tabletop Game](https://arxiv.org/abs/2006.02716)
# Dominion
- [Clustering Player Strategies from Variable-Length Game Logs in Dominion](https://arxiv.org/abs/1811.11273)
# Mafia
- [A mathematical model of the Mafia game](https://arxiv.org/abs/1009.1031)
- [Automatic Long-Term Deception Detection in Group Interaction Videos](https://arxiv.org/abs/1905.08617)
# The Resistance: Avalon
- [Finding Friend and Foe in Multi-Agent Games](https://arxiv.org/abs/1906.02330)
# Ticket to Ride
- [Evolving maps and decks for ticket to ride](https://doi.org/10.1145/3235765.3235813)
- [Materials for Ticket to Ride Seattle and a framework for making more game boards](https://github.com/dovinmu/ttr_generator)
- [Applications of Graph Theory andProbability in the Board GameTicket toRide](https://www.rtealwitter.com/slides/2020-JMM.pdf)
- [The Difficulty of Learning Ticket to Ride](https://www.eecs.tufts.edu/~jsinapov/teaching/comp150_RL/reports/Nguyen_Dinjian_report.pdf)