# boardgame-research [![PRs Welcome](https://img.shields.io/badge/PRs-welcome-brightgreen.svg?style=flat-square)](http://makeapullrequest.com) This is a list of boardgame research. They are primarily related to "solving/playing/learning" games (by various different approaches), or occasionaly about designing or meta-aspects of the game. This doesn't cover all aspects of each game (notably missing social-science stuff), but should be of interest to anyone interested in boardgames and their optimal play. While there is a ton of easily accessible research on games like 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 list also covers some computer-games that fall under similar themes. Exported versions are available in the following formats: - [Zotero RDF](boardgame-research.rdf) - [BibTeX](boardgame-research.bib) Watch the repository to get the latest updates for now. If you aren't able to access any paper on this list, please [try using Sci-Hub](https://en.wikipedia.org/wiki/Sci-Hub) or [reach out to me](https://captnemo.in/contact/). - [Accessibility](#accessibility) - [Carcassonne](#carcassonne) - [Diplomacy](#diplomacy) - [Dixit](#dixit) - [Hanabi](#hanabi) - [Hive](#hive) - [Jenga](#jenga) - [Kingdomino](#kingdomino) - [Mafia](#mafia) - [Magic: The Gathering](#magic-the-gathering) - [Mobile Games](#mobile-games) - [2048](#2048) - [Monopoly](#monopoly) - [Monopoly Deal](#monopoly-deal) - [Nmbr9](#nmbr9) - [Patchwork](#patchwork) - [Quixo](#quixo) - [Race for the Galaxy](#race-for-the-galaxy) - [RISK](#risk) - [Secret Hitler](#secret-hitler) - [Set](#set) - [Settlers of Catan](#settlers-of-catan) - [Shobu](#shobu) - [Terra Mystica](#terra-mystica) - [Tetris Link](#tetris-link) - [Ticket to Ride](#ticket-to-ride) - [Ultimate Tic-Tac-Toe](#ultimate-tic-tac-toe) - [UNO](#uno) - [Yahtzee](#yahtzee) # Accessibility - [Meeple Centred Design: A Heuristic Toolkit for Evaluating the Accessibility of Tabletop Games](http://link.springer.com/10.1007/s40869-018-0057-8) (journalArticle) - [Eighteen Months of Meeple Like Us: An Exploration into the State of Board Game Accessibility](http://link.springer.com/10.1007/s40869-018-0056-9) (journalArticle) # Carcassonne - [Playing Carcassonne with Monte Carlo Tree Search](http://arxiv.org/abs/2009.12974) (journalArticle) # Diplomacy - [Learning to Play No-Press Diplomacy with Best Response Policy Iteration](http://arxiv.org/abs/2006.04635v2) (journalArticle) - [No Press Diplomacy: Modeling Multi-Agent Gameplay](http://arxiv.org/abs/1909.02128v2) (journalArticle) - [Agent Madoff: A Heuristic-Based Negotiation Agent For The Diplomacy Strategy Game](http://arxiv.org/abs/1902.06996v1) (journalArticle) - [Monte Carlo Tree Search for the Game of Diplomacy](https://dl.acm.org/doi/10.1145/3411408.3411413) (conferencePaper) # Dixit - [Creative Captioning: An AI Grand Challenge Based on the Dixit Board Game](http://arxiv.org/abs/2010.00048) (journalArticle) # Hanabi - [How to Make the Perfect Fireworks Display: Two Strategies forHanabi](https://doi.org/10.4169%2Fmath.mag.88.5.323) (journalArticle) - [Evaluating and modelling Hanabi-playing agents](https://doi.org/10.1109%2Fcec.2017.7969465) (conferencePaper) - [The Hanabi challenge: A new frontier for AI research](https://doi.org/10.1016%2Fj.artint.2019.103216) (journalArticle) - [The 2018 Hanabi competition](https://doi.org/10.1109%2Fcig.2019.8848008) (conferencePaper) - [Diverse Agents for Ad-Hoc Cooperation in Hanabi](https://doi.org/10.1109%2Fcig.2019.8847944) (conferencePaper) - [Improving Policies via Search in Cooperative Partially Observable Games](http://arxiv.org/abs/1912.02318v1) (journalArticle) - [Hanabi is NP-hard, Even for Cheaters who Look at Their Cards](http://arxiv.org/abs/1603.01911v3) (journalArticle) - [Generating and Adapting to Diverse Ad-Hoc Cooperation Agents in Hanabi](http://arxiv.org/abs/2004.13710v2) (journalArticle) - [Evaluating the Rainbow DQN Agent in Hanabi with Unseen Partners](http://arxiv.org/abs/2004.13291v1) (journalArticle) - [Re-determinizing MCTS in Hanabi]() (conferencePaper) - [Evolving Agents for the Hanabi 2018 CIG Competition](https://ieeexplore.ieee.org/document/8490449/) (conferencePaper) - [Aspects of the Cooperative Card Game Hanabi](http://link.springer.com/10.1007/978-3-319-67468-1_7) (bookSection) - [Playing Hanabi Near-Optimally](http://link.springer.com/10.1007/978-3-319-71649-7_5) (bookSection) - [An intentional AI for hanabi](http://ieeexplore.ieee.org/document/8080417/) (conferencePaper) - [Solving Hanabi: Estimating Hands by Opponent's Actions in Cooperative Game with Incomplete Information](https://aaai.org/ocs/index.php/WS/AAAIW15/paper/view/10167) (conferencePaper) - [A Browser-based Interface for the Exploration and Evaluation of Hanabi AIs](http://fdg2017.org/papers/FDG2017_demo_Hanabi.pdf) (journalArticle) - [I see what you see: Integrating eye tracking into Hanabi playing agents]() (journalArticle) - [State of the art Hanabi bots + simulation framework in rust](https://github.com/WuTheFWasThat/hanabi.rs) (computerProgram) - [A strategy simulator for the well-known cooperative card game Hanabi](https://github.com/rjtobin/HanSim) (computerProgram) - [A framework for writing bots that play Hanabi](https://github.com/Quuxplusone/Hanabi) (computerProgram) - [Operationalizing Intentionality to Play Hanabi with Human Players](https://ieeexplore.ieee.org/document/9140404/) (journalArticle) - [Behavioral Evaluation of Hanabi Rainbow DQN Agents and Rule-Based Agents](https://ojs.aaai.org/index.php/AIIDE/article/view/7404) (journalArticle) - [Playing mini-Hanabi card game with Q-learning](http://id.nii.ac.jp/1001/00205046/) (conferencePaper) # Hive - [On the complexity of Hive](https://dspace.library.uu.nl/handle/1874/396955) (thesis) # Jenga - [Jidoukan Jenga: Teaching English through remixing games and game rules](https://www.llpjournal.org/2020/04/13/jidokan-jenga.html) (journalArticle) # Kingdomino - [Monte Carlo Methods for the Game Kingdomino](https://doi.org/10.1109%2Fcig.2018.8490419) (conferencePaper) - [Monte Carlo Methods for the Game Kingdomino](http://arxiv.org/abs/1807.04458v2) (journalArticle) - [NP-completeness of the game Kingdomino](http://arxiv.org/abs/1909.02849v3) (journalArticle) # Mafia - [A mathematical model of the Mafia game](http://arxiv.org/abs/1009.1031v3) (journalArticle) # Magic: The Gathering - [Ensemble Determinization in Monte Carlo Tree Search for the Imperfect Information Card Game Magic: The Gathering](https://doi.org/10.1109%2Ftciaig.2012.2204883) (journalArticle) - [Optimal Card-Collecting Strategies for Magic: The Gathering](https://doi.org/10.1080%2F07468342.2000.11974103) (journalArticle) - [Monte Carlo search applied to card selection in Magic: The Gathering](https://doi.org/10.1109%2Fcig.2009.5286501) (conferencePaper) - [Magic: the Gathering is as Hard as Arithmetic](http://arxiv.org/abs/2003.05119v1) (journalArticle) - [Magic: The Gathering is Turing Complete](http://arxiv.org/abs/1904.09828v2) (journalArticle) - [Neural Networks Models for Analyzing Magic: the Gathering Cards](http://arxiv.org/abs/1810.03744v1) (journalArticle) # Mobile Games - [2048]() () - [Trainyard is NP-Hard](http://arxiv.org/abs/1603.00928v1) (journalArticle) - [Threes!, Fives, 1024!, and 2048 are Hard](http://arxiv.org/abs/1505.04274v1) (journalArticle) # 2048 - [Ensemble Determinization in Monte Carlo Tree Search for the Imperfect Information Card Game Magic: The Gathering](https://doi.org/10.1109%2Ftciaig.2012.2204883) (journalArticle) - [Systematic Selection of N-Tuple Networks for 2048](https://doi.org/10.1007%2F978-3-319-50935-8_8) (bookSection) - [Systematic selection of N-tuple networks with consideration of interinfluence for game 2048](https://doi.org/10.1109%2Ftaai.2016.7880154) (conferencePaper) - [An investigation into 2048 AI strategies](https://doi.org/10.1109%2Fcig.2014.6932920) (conferencePaper) - [Threes!, Fives, 1024!, and 2048 are Hard](http://arxiv.org/abs/1505.04274v1) (journalArticle) - [Making Change in 2048](http://arxiv.org/abs/1804.07396v1) (journalArticle) - [Analysis of the Game "2048" and its Generalization in Higher Dimensions](http://arxiv.org/abs/1804.07393v2) (journalArticle) - [Multi-Stage Temporal Difference Learning for 2048-like Games](http://arxiv.org/abs/1606.07374v2) (journalArticle) - [2048 is (PSPACE) Hard, but Sometimes Easy](http://arxiv.org/abs/1408.6315v1) (journalArticle) - [Ensemble Determinization in Monte Carlo Tree Search for the Imperfect Information Card Game Magic: The Gathering](https://doi.org/10.1109%2Ftciaig.2012.2204883) (journalArticle) - [Systematic Selection of N-Tuple Networks for 2048](https://doi.org/10.1007%2F978-3-319-50935-8_8) (bookSection) - [Systematic selection of N-tuple networks with consideration of interinfluence for game 2048](https://doi.org/10.1109%2Ftaai.2016.7880154) (conferencePaper) - [An investigation into 2048 AI strategies](https://doi.org/10.1109%2Fcig.2014.6932920) (conferencePaper) - [Threes!, Fives, 1024!, and 2048 are Hard](http://arxiv.org/abs/1505.04274v1) (journalArticle) - [Making Change in 2048](http://arxiv.org/abs/1804.07396v1) (journalArticle) - [Analysis of the Game "2048" and its Generalization in Higher Dimensions](http://arxiv.org/abs/1804.07393v2) (journalArticle) - [Multi-Stage Temporal Difference Learning for 2048-like Games](http://arxiv.org/abs/1606.07374v2) (journalArticle) - [2048 is (PSPACE) Hard, but Sometimes Easy](http://arxiv.org/abs/1408.6315v1) (journalArticle) # Monopoly - [Monopoly as a Markov Process](https://doi.org/10.1080%2F0025570x.1972.11976187) (journalArticle) # Monopoly Deal - [Implementation of Artificial Intelligence with 3 Different Characters of AI Player on “Monopoly Deal” Computer Game](https://doi.org/10.1007%2F978-3-662-46742-8_11) (bookSection) # Nmbr9 - [Nmbr9 as a Constraint Programming Challenge](http://arxiv.org/abs/2001.04238) (journalArticle) - [Nmbr9 as a Constraint Programming Challenge](https://zayenz.se/blog/post/nmbr9-cp2019-abstract/) (blogPost) # Patchwork - [State Representation and Polyomino Placement for the Game Patchwork](https://zayenz.se/blog/post/patchwork-modref2019-paper/) (blogPost) - [State Representation and Polyomino Placement for the Game Patchwork](http://arxiv.org/abs/2001.04233) (journalArticle) - [State Representation and Polyomino Placement for the Game Patchwork](https://zayenz.se/papers/Lagerkvist_ModRef_2019_Presentation.pdf) (presentation) # Quixo - [QUIXO is EXPTIME-complete](https://doi.org/10.1016%2Fj.ipl.2020.105995) (journalArticle) - [Quixo Is Solved](http://arxiv.org/abs/2007.15895) (journalArticle) # Race for the Galaxy - [SCOUT: A Case-Based Reasoning Agent for Playing Race for the Galaxy](https://doi.org/10.1007%2F978-3-319-61030-6_27) (bookSection) # RISK - [Mini-Risk: Strategies for a Simplified Board Game](https://doi.org/10.1057%2Fjors.1990.2) (journalArticle) - [Learning the risk board game with classifier systems](https://doi.org/10.1145%2F508791.508904) (conferencePaper) - [Markov Chains and the RISK Board Game](https://doi.org/10.1080%2F0025570x.1997.11996573) (journalArticle) - [Markov Chains for the RISK Board Game Revisited](https://doi.org/10.1080%2F0025570x.2003.11953165) (journalArticle) - [Planning an Endgame Move Set for the Game RISK: A Comparison of Search Algorithms](https://doi.org/10.1109%2Ftevc.2005.856211) (journalArticle) - [An Intelligent Artificial Player for the Game of Risk](http://www.ke.tu-darmstadt.de/lehre/archiv/ss04/oberseminar/folien/Wolf_Michael-Slides.pdf) (presentation) - [RISKy Business: An In-Depth Look at the Game RISK](https://scholar.rose-hulman.edu/rhumj/vol3/iss2/3) (journalArticle) - [RISK Board Game ‐ Battle Outcome Analysis](http://www.c4i.gr/xgeorgio/docs/RISK-board-game%20_rev-3.pdf) (journalArticle) - [A multi-agent system for playing the board game risk]() (book) # Secret Hitler - [Competing in a Complex Hidden Role Game with Information Set Monte Carlo Tree Search](http://arxiv.org/abs/2005.07156) (journalArticle) # Set - [Game, Set, Math](https://doi.org/10.4169%2Fmath.mag.85.2.083) (journalArticle) - [The Joy of SET](https://doi.org/10.1080%2F00029890.2018.1412661) (journalArticle) # Settlers of Catan - [The effectiveness of persuasion in The Settlers of Catan](http://ieeexplore.ieee.org/document/6932861/) (conferencePaper) - [The effectiveness of persuasion in The Settlers of Catan](https://doi.org/10.1109%2Fcig.2014.6932861) (conferencePaper) - [Avoiding Revenge Using Optimal Opponent Ranking Strategy in the Board Game Catan](https://doi.org/10.4018%2Fijgcms.2018040103) (journalArticle) - [Game strategies for The Settlers of Catan](https://doi.org/10.1109%2Fcig.2014.6932884) (conferencePaper) - [Monte-Carlo Tree Search in Settlers of Catan](https://doi.org/10.1007%2F978-3-642-12993-3_3) (bookSection) - [Deep Reinforcement Learning in Strategic Board Game Environments](https://doi.org/10.1007%2F978-3-030-14174-5_16) (bookSection) - [Settlers of Catan bot trained using reinforcement learning](https://jonzia.github.io/Catan/) (computerProgram) - [Trading in a multiplayer board game: Towards an analysis of non-cooperative dialogue]() (conferencePaper) - [POMCP with Human Preferencesin Settlers of Catan](https://www.aaai.org/ocs/index.php/AIIDE/AIIDE18/paper/viewFile/18091/17217) (journalArticle) - [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) (blogPost) - [Monte Carlo Tree Search in a Modern Board Game Framework](https://project.dke.maastrichtuniversity.nl/games/files/bsc/Roelofs_Bsc-paper.pdf) (journalArticle) - [Reinforcement Learning of Strategies for Settlers of Catan]() (book) - [Playing Catan with Cross-dimensional Neural Network](http://arxiv.org/abs/2008.07079) (journalArticle) # Shobu - [Shobu AI Playground](https://github.com/JayWalker512/Shobu) (computerProgram) - [Shobu randomly played games dataset](https://www.kaggle.com/bsfoltz/shobu-randomly-played-games-104k) (webpage) # Terra Mystica - [Using Tabu Search Algorithm for Map Generation in the Terra Mystica Tabletop Game](https://doi.org/10.1145%2F3396474.3396492) (conferencePaper) # Tetris Link - [A New Challenge: Approaching Tetris Link with AI](http://arxiv.org/abs/2004.00377) (journalArticle) # Ticket to Ride - [AI-based playtesting of contemporary board games](http://dl.acm.org/citation.cfm?doid=3102071.3102105) (conferencePaper) - [Materials for Ticket to Ride Seattle and a framework for making more game boards](https://github.com/dovinmu/ttr_generator) (computerProgram) - [https://www.eecs.tufts.edu/~jsinapov/teaching/comp150_RL/reports/Nguyen_Dinjian_report.pdf](https://www.eecs.tufts.edu/~jsinapov/teaching/comp150_RL/reports/Nguyen_Dinjian_report.pdf) (report) - [Evolving maps and decks for ticket to ride](https://dl.acm.org/doi/10.1145/3235765.3235813) (conferencePaper) - [Applications of Graph Theory andProbability in the Board GameTicket toRide](https://www.rtealwitter.com/slides/2020-JMM.pdf) (presentation) # Ultimate Tic-Tac-Toe - [At Most 43 Moves, At Least 29: Optimal Strategies and Bounds for Ultimate Tic-Tac-Toe](http://arxiv.org/abs/2006.02353) (journalArticle) # UNO - [UNO Is Hard, Even for a Single Player](https://doi.org/10.1007%2F978-3-642-13122-6_15) (bookSection) - [The complexity of UNO](http://arxiv.org/abs/1003.2851v3) (journalArticle) # Yahtzee - [Nearly Optimal Computer Play in Multi-player Yahtzee](https://doi.org/10.1007%2F978-3-642-17928-0_23) (bookSection) - [Computer Strategies for Solitaire Yahtzee](https://doi.org/10.1109%2Fcig.2007.368089) (conferencePaper) - [Modeling expert problem solving in a game of chance: a Yahtzeec case study](https://doi.org/10.1111%2F1468-0394.00160) (journalArticle)