Sort games alphabetically
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**Table of Contents** *generated with [DocToc](https://github.com/thlorenz/doctoc)*
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- [Settlers of Catan](#settlers-of-catan)
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- [Modern Art: The card game](#modern-art-the-card-game)
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- [Diplomacy](#diplomacy)
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- [Risk](#risk)
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- [Kingdomino](#kingdomino)
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- [Patchwork](#patchwork)
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- [Nmbr9](#nmbr9)
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- [Hanabi](#hanabi)
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- [Azul](#azul)
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- [Monopoly](#monopoly)
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- [Magic: the Gathering](#magic-the-gathering)
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- [Terra Mystica](#terra-mystica)
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- [Mafia](#mafia)
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- [The Resistance: Avalon](#the-resistance-avalon)
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- [Ticket to Ride](#ticket-to-ride)
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- [Lost Cities](#lost-cities)
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- [Uno](#uno)
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- [Blokus](#blokus)
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- [Diplomacy](#diplomacy)
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- [Dominion](#dominion)
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- [Hanabi](#hanabi)
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- [Settlers of Catan](#settlers-of-catan)
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- [Kingdomino](#kingdomino)
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- [Lost Cities](#lost-cities)
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- [Mafia](#mafia)
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- [Magic: the Gathering](#magic-the-gathering)
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- [Modern Art: The card game](#modern-art-the-card-game)
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- [Monopoly](#monopoly)
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- [Monopoly Deal](#monopoly-deal)
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- [Nmbr9](#nmbr9)
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- [Pandemic](#pandemic)
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- [Patchwork](#patchwork)
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- [Pentago](#pentago)
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- [Quixo](#quixo)
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- [Race for the Galaxy](#race-for-the-galaxy)
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- [The Resistance: Avalon](#the-resistance-avalon)
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- [Risk](#risk)
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- [Santorini](#santorini)
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- [Set](#set)
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- [Pentago](#pentago)
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- [Blokus](#blokus)
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- [Pandemic](#pandemic)
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- [Scotland Yard](#scotland-yard)
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- [Monopoly Deal](#monopoly-deal)
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- [Set](#set)
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- [Terra Mystica](#terra-mystica)
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- [Ticket to Ride](#ticket-to-ride)
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- [Uno](#uno)
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- [Yahtzee](#yahtzee)
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- [Mobile Games](#mobile-games)
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- [2048](#2048)
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@ -55,47 +55,23 @@ If you aren't able to access any paper on this list, please [try using Sci-Hub](
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<!-- END doctoc generated TOC please keep comment here to allow auto update -->
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# Settlers of Catan
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- [The effectiveness of persuasion in The Settlers of Catan ](https://doi.org/10.1109/CIG.2014.6932861)
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- [Avoiding Revenge Using Optimal Opponent Ranking Strategy in the Board Game Catan ](https://doi.org/10.4018/IJGCMS.2018040103)
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- [Game strategies for The Settlers of Catan](https://doi.org/10.1109/CIG.2014.6932884)
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- [Monte-Carlo Tree Search in Settlers of Catan](https://doi.org/10.1007/978-3-642-12993-3_3)
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- [Settlers of Catan bot trained using reinforcement learning (MATLAB).](https://jonzia.github.io/Catan/)
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- [Trading in a multiplayer board game: Towards an analysis of non-cooperative dialogue](https://escholarship.org/content/qt9zt506xx/qt9zt506xx.pdf)
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- [POMCP with Human Preferencesin Settlers of Catan](https://www.aaai.org/ocs/index.php/AIIDE/AIIDE18/paper/viewFile/18091/17217)
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- [Reinforcement Learning of Strategies for Settlers of Catan](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.561.6293&rep=rep1&type=pdf)
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- [Deep Reinforcement Learning in Strategic Board GameEnvironments](https://doi.org/10.1007/978-3-030-14174-5_16) [[pdf](https://hal.archives-ouvertes.fr/hal-02124411/document)]
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- [Monte Carlo Tree Search in a Modern Board Game Framework](https://project.dke.maastrichtuniversity.nl/games/files/bsc/Roelofs_Bsc-paper.pdf)
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- [The impact of loaded dice in Catan](https://izbicki.me/blog/how-to-cheat-at-settlers-of-catan-by-loading-the-dice-and-prove-it-with-p-values.html)
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# Azul
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- [A summary of a dissertation on Azul](https://old.reddit.com/r/boardgames/comments/hxodaf/update_i_wrote_my_dissertation_on_azul/fzd3961/?context=3) (unpublished)
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# Modern Art: The card game
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- [A constraint programming based solver for Modern Art](https://github.com/captn3m0/modernart)
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# Blokus
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- [Blokus Game Solver](https://digitalcommons.calpoly.edu/cpesp/290/)
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# Diplomacy
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- [Learning to Play No-Press Diplomacy with Best Response Policy Iteration ](https://arxiv.org/abs/2006.04635)
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- [No Press Diplomacy: Modeling Multi-Agent Gameplay ](https://arxiv.org/abs/1909.02128)
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- [Agent Madoff: A Heuristic-Based Negotiation Agent For The Diplomacy Strategy Game ](https://arxiv.org/abs/1902.06996)
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# Risk
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- [Mini-Risk: Strategies for a Simplified Board Game](https://doi.org/10.1057/jors.1990.2)
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- [A Multi-Agent System for playing the board game Risk](https://www.diva-portal.org/smash/record.jsf?pid=diva2%3A831093&dswid=-4740)
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- [Learning the risk board game with classifier systems](https://doi.org/10.1145/508791.508904)
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- [Markov Chains and the RISK Board Game](https://doi.org/10.1080/0025570X.1997.11996573)
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- [Markov Chains for the RISK Board Game Revisited](https://doi.org/10.1080/0025570X.2003.11953165)
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- [RISK Board Game ‐ Battle Outcome Analysis](http://www.c4i.gr/xgeorgio/docs/RISK-board-game%20_rev-3.pdf)
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- [Planning an endgame move set for the game RISK](https://doi.org/10.1109/TEVC.2005.856211)
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- [RISKy Business: An In-Depth Look at the Game RISK](https://scholar.rose-hulman.edu/rhumj/vol3/iss2/3/)
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- [An Intelligent Artificial Player for the Game of Risk](http://www.ke.tu-darmstadt.de/lehre/archiv/ss04/oberseminar/folien/Wolf_Michael-Slides.pdf)
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# Dominion
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# Kingdomino
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- [Monte Carlo Methods for the Game Kingdomino](https://doi.org/10.1109/CIG.2018.8490419) [[arXiv](https://arxiv.org/abs/1807.04458)]
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- [NP-completeness of the game Kingdomino](https://arxiv.org/abs/1909.02849)
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There is a [simulator](https://dominionsimulator.wordpress.com/f-a-q/) and the code behind
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[the Dominion server running councilroom.com](https://github.com/mikemccllstr/dominionstats/) is available. councilroom has the [best and worst openings](http://councilroom.com/openings), [optimal card ratios](http://councilroom.com/optimal_card_ratios), [Card winning stats](http://councilroom.com/supply_win) and lots of other empirical research.
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# Patchwork
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- [State Representation and Polyomino Placement for the Game Patchwork](https://zayenz.se/blog/post/patchwork-modref2019-paper/)
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# Nmbr9
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- [Nmbr9 as a Constraint Programming Challenge](https://zayenz.se/blog/post/nmbr9-cp2019-abstract/)
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- [Clustering Player Strategies from Variable-Length Game Logs in Dominion](https://arxiv.org/abs/1811.11273)
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# Hanabi
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- [Improving Policies via Search in Cooperative Partially Observable Games](https://arxiv.org/abs/1912.02318) (FB) [[code](https://github.com/facebookresearch/Hanabi_SPARTA)] - Current best result.
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@ -118,19 +94,17 @@ If you aren't able to access any paper on this list, please [try using Sci-Hub](
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- [A framework for writing bots that play Hanabi](https://github.com/Quuxplusone/Hanabi)
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- [Evaluating the Rainbow DQN Agent in Hanabi with Unseen Partners](https://arxiv.org/abs/2004.13291)
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# Azul
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- [A summary of a dissertation on Azul](https://old.reddit.com/r/boardgames/comments/hxodaf/update_i_wrote_my_dissertation_on_azul/fzd3961/?context=3) (unpublished)
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# Kingdomino
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- [Monte Carlo Methods for the Game Kingdomino](https://doi.org/10.1109/CIG.2018.8490419) [[arXiv](https://arxiv.org/abs/1807.04458)]
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- [NP-completeness of the game Kingdomino](https://arxiv.org/abs/1909.02849)
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# Monopoly
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- [Negotiation strategy of agents in the MONOPOLY game](https://ieeexplore.ieee.org/abstract/document/1013210)
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- [Generating interesting Monopoly boards from open data](https://ieeexplore.ieee.org/abstract/document/6374168)
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- [Estimating the probability that the game of Monopoly never ends](https://ieeexplore.ieee.org/abstract/document/5429349)
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- [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)
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- [Monopoly as a Markov Process](https://doi.org/10.1080/0025570X.1972.11976187)
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- [Learning to Play Monopoly withMonte Carlo Tree Search](https://project-archive.inf.ed.ac.uk/ug4/20181042/ug4_proj.pdf)
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- [Monopoly Using Reinforcement Learning ](https://ieeexplore.ieee.org/abstract/document/8929523)
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- [A Markovian Exploration of Monopoly](https://pi4.math.illinois.edu/wp-content/uploads/2014/10/Gartland-Burson-Ferguson-Markovopoly.pdf)
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- [What's the best Monopoly strategy](https://publications.lakeforest.edu/cgi/viewcontent.cgi?referer=&httpsredir=1&article=1277&context=gss)
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# Lost Cities
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- [Applying Neural Networks and Genetic Programming to the Game Lost Cities](http://digital.library.wisc.edu/1793/79080)
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# Mafia
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- [A mathematical model of the Mafia game](https://arxiv.org/abs/1009.1031)
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- [Automatic Long-Term Deception Detection in Group Interaction Videos](https://arxiv.org/abs/1905.08617)
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- [Human-Side Strategies in the Werewolf Game Against the Stealth Werewolf Strategy](https://link.springer.com/chapter/10.1007/978-3-319-50935-8_9)
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# Magic: the Gathering
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- [Magic: the Gathering is as Hard as Arithmetic](https://arxiv.org/abs/2003.05119)
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@ -146,36 +120,34 @@ If you aren't able to access any paper on this list, please [try using Sci-Hub](
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- [Monte Carlo search applied to card selection in Magic: The Gathering](https://doi.org/10.1109/CIG.2009.5286501)
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- [Magic: The Gathering Deck Performance Prediction](http://cs229.stanford.edu/proj2012/HauPlotkinTran-MagicTheGatheringDeckPerformancePrediction.pdf)
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# Terra Mystica
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- [Using Tabu Search Algorithm for Map Generation in the Terra Mystica Tabletop Game](https://arxiv.org/abs/2006.02716)
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# Modern Art: The card game
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- [A constraint programming based solver for Modern Art](https://github.com/captn3m0/modernart)
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# Mafia
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- [A mathematical model of the Mafia game](https://arxiv.org/abs/1009.1031)
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- [Automatic Long-Term Deception Detection in Group Interaction Videos](https://arxiv.org/abs/1905.08617)
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- [Human-Side Strategies in the Werewolf Game Against the Stealth Werewolf Strategy](https://link.springer.com/chapter/10.1007/978-3-319-50935-8_9)
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# Monopoly
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- [Negotiation strategy of agents in the MONOPOLY game](https://ieeexplore.ieee.org/abstract/document/1013210)
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- [Generating interesting Monopoly boards from open data](https://ieeexplore.ieee.org/abstract/document/6374168)
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- [Estimating the probability that the game of Monopoly never ends](https://ieeexplore.ieee.org/abstract/document/5429349)
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- [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)
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- [Monopoly as a Markov Process](https://doi.org/10.1080/0025570X.1972.11976187)
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- [Learning to Play Monopoly withMonte Carlo Tree Search](https://project-archive.inf.ed.ac.uk/ug4/20181042/ug4_proj.pdf)
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- [Monopoly Using Reinforcement Learning ](https://ieeexplore.ieee.org/abstract/document/8929523)
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- [A Markovian Exploration of Monopoly](https://pi4.math.illinois.edu/wp-content/uploads/2014/10/Gartland-Burson-Ferguson-Markovopoly.pdf)
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- [What's the best Monopoly strategy](https://publications.lakeforest.edu/cgi/viewcontent.cgi?referer=&httpsredir=1&article=1277&context=gss)
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# The Resistance: Avalon
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- [Finding Friend and Foe in Multi-Agent Games](https://arxiv.org/abs/1906.02330)
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# Monopoly Deal
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- [Implementation of AI Player on "Monopoly Deal"](https://doi.org/10.1007/978-3-662-46742-8_11)
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# Ticket to Ride
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- [Evolving maps and decks for ticket to ride](https://doi.org/10.1145/3235765.3235813)
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- [Materials for Ticket to Ride Seattle and a framework for making more game boards](https://github.com/dovinmu/ttr_generator)
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- [Applications of Graph Theory andProbability in the Board GameTicket toRide](https://www.rtealwitter.com/slides/2020-JMM.pdf)
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- [The Difficulty of Learning Ticket to Ride](https://www.eecs.tufts.edu/~jsinapov/teaching/comp150_RL/reports/Nguyen_Dinjian_report.pdf)
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# Nmbr9
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- [Nmbr9 as a Constraint Programming Challenge](https://zayenz.se/blog/post/nmbr9-cp2019-abstract/)
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# Lost Cities
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- [Applying Neural Networks and Genetic Programming to the Game Lost Cities](http://digital.library.wisc.edu/1793/79080)
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# Pandemic
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- [NP-Completeness of Pandemic](https://www.jstage.jst.go.jp/article/ipsjjip/20/3/20_723/_article)
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# Uno
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- [The complexity of UNO](https://arxiv.org/abs/1003.2851)
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- [UNO Is Hard, Even for a Single Player](https://doi.org/10.1007/978-3-642-13122-6_15)
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# Patchwork
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- [State Representation and Polyomino Placement for the Game Patchwork](https://zayenz.se/blog/post/patchwork-modref2019-paper/)
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# Dominion
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There is a [simulator](https://dominionsimulator.wordpress.com/f-a-q/) and the code behind
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[the Dominion server running councilroom.com](https://github.com/mikemccllstr/dominionstats/) is available. councilroom has the [best and worst openings](http://councilroom.com/openings), [optimal card ratios](http://councilroom.com/optimal_card_ratios), [Card winning stats](http://councilroom.com/supply_win) and lots of other empirical research.
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- [Clustering Player Strategies from Variable-Length Game Logs in Dominion](https://arxiv.org/abs/1811.11273)
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# Pentago
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- [On Solving Pentago](http://www.ke.tu-darmstadt.de/lehre/arbeiten/bachelor/2011/Buescher_Niklas.pdf)
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# Quixo
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- [QUIXO is EXPTIME-complete](https://doi.org/10.1016/j.ipl.2020.105995)
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# Race for the Galaxy
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- [SCOUT: A Case-Based Reasoning Agent for Playing Race for the Galaxy](https://doi.org/10.1007/978-3-319-61030-6_27)
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# The Resistance: Avalon
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- [Finding Friend and Foe in Multi-Agent Games](https://arxiv.org/abs/1906.02330)
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# Risk
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- [Mini-Risk: Strategies for a Simplified Board Game](https://doi.org/10.1057/jors.1990.2)
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- [A Multi-Agent System for playing the board game Risk](https://www.diva-portal.org/smash/record.jsf?pid=diva2%3A831093&dswid=-4740)
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- [Learning the risk board game with classifier systems](https://doi.org/10.1145/508791.508904)
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- [Markov Chains and the RISK Board Game](https://doi.org/10.1080/0025570X.1997.11996573)
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- [Markov Chains for the RISK Board Game Revisited](https://doi.org/10.1080/0025570X.2003.11953165)
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- [RISK Board Game ‐ Battle Outcome Analysis](http://www.c4i.gr/xgeorgio/docs/RISK-board-game%20_rev-3.pdf)
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- [Planning an endgame move set for the game RISK](https://doi.org/10.1109/TEVC.2005.856211)
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- [RISKy Business: An In-Depth Look at the Game RISK](https://scholar.rose-hulman.edu/rhumj/vol3/iss2/3/)
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- [An Intelligent Artificial Player for the Game of Risk](http://www.ke.tu-darmstadt.de/lehre/archiv/ss04/oberseminar/folien/Wolf_Michael-Slides.pdf)
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# Santorini
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- [A Mathematical Analysis of the Game of Santorini](https://openworks.wooster.edu/independentstudy/8917/)
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# Set
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# Scotland Yard
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- [The complexity of Scotland Yard](http://www.illc.uva.nl/Research/Publications/Reports/PP-2006-18.text.pdf)
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# Set
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Set has a long history of mathematical research, so this list isn't exhaustive.
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- [Game, Set, Math](https://doi.org/10.4169/math.mag.85.2.083)
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- [The Joy of SET](https://doi.org/10.1080/00029890.2018.1412661)
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# Pentago
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- [On Solving Pentago](http://www.ke.tu-darmstadt.de/lehre/arbeiten/bachelor/2011/Buescher_Niklas.pdf)
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# Settlers of Catan
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- [The effectiveness of persuasion in The Settlers of Catan ](https://doi.org/10.1109/CIG.2014.6932861)
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- [Avoiding Revenge Using Optimal Opponent Ranking Strategy in the Board Game Catan ](https://doi.org/10.4018/IJGCMS.2018040103)
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- [Game strategies for The Settlers of Catan](https://doi.org/10.1109/CIG.2014.6932884)
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- [Monte-Carlo Tree Search in Settlers of Catan](https://doi.org/10.1007/978-3-642-12993-3_3)
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- [Settlers of Catan bot trained using reinforcement learning (MATLAB).](https://jonzia.github.io/Catan/)
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- [Trading in a multiplayer board game: Towards an analysis of non-cooperative dialogue](https://escholarship.org/content/qt9zt506xx/qt9zt506xx.pdf)
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- [POMCP with Human Preferencesin Settlers of Catan](https://www.aaai.org/ocs/index.php/AIIDE/AIIDE18/paper/viewFile/18091/17217)
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- [Reinforcement Learning of Strategies for Settlers of Catan](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.561.6293&rep=rep1&type=pdf)
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- [Deep Reinforcement Learning in Strategic Board GameEnvironments](https://doi.org/10.1007/978-3-030-14174-5_16) [[pdf](https://hal.archives-ouvertes.fr/hal-02124411/document)]
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- [Monte Carlo Tree Search in a Modern Board Game Framework](https://project.dke.maastrichtuniversity.nl/games/files/bsc/Roelofs_Bsc-paper.pdf)
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- [The impact of loaded dice in Catan](https://izbicki.me/blog/how-to-cheat-at-settlers-of-catan-by-loading-the-dice-and-prove-it-with-p-values.html)
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# Blokus
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- [Blokus Game Solver](https://digitalcommons.calpoly.edu/cpesp/290/)
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# Terra Mystica
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- [Using Tabu Search Algorithm for Map Generation in the Terra Mystica Tabletop Game](https://arxiv.org/abs/2006.02716)
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# Pandemic
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- [NP-Completeness of Pandemic](https://www.jstage.jst.go.jp/article/ipsjjip/20/3/20_723/_article)
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# Ticket to Ride
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- [Evolving maps and decks for ticket to ride](https://doi.org/10.1145/3235765.3235813)
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- [Materials for Ticket to Ride Seattle and a framework for making more game boards](https://github.com/dovinmu/ttr_generator)
|
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- [Applications of Graph Theory andProbability in the Board GameTicket toRide](https://www.rtealwitter.com/slides/2020-JMM.pdf)
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- [The Difficulty of Learning Ticket to Ride](https://www.eecs.tufts.edu/~jsinapov/teaching/comp150_RL/reports/Nguyen_Dinjian_report.pdf)
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# Scotland Yard
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- [The complexity of Scotland Yard](http://www.illc.uva.nl/Research/Publications/Reports/PP-2006-18.text.pdf)
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# Monopoly Deal
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- [Implementation of AI Player on "Monopoly Deal"](https://doi.org/10.1007/978-3-662-46742-8_11)
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# Uno
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- [The complexity of UNO](https://arxiv.org/abs/1003.2851)
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- [UNO Is Hard, Even for a Single Player](https://doi.org/10.1007/978-3-642-13122-6_15)
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# Yahtzee
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- [Optimal Solitaire Yahtzee Strategies](http://www.yahtzee.org.uk/optimal_yahtzee_TV.pdf)
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Reference in New Issue