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# 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.
An importable RDF version is available as well:
- [Zotero RDF](boardgame-research.rdf)
See Import instructions here: https://www.zotero.org/support/kb/importing_standardized_formats
[Watch the repository](https://docs.github.com/en/github/managing-subscriptions-and-notifications-on-github/setting-up-notifications/configuring-notifications#configuring-your-watch-settings-for-an-individual-repository) to get the latest updates for now (Choose "All Activity").
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/).
<!-- START doctoc generated TOC please keep comment here to allow auto update -->
<!-- DON'T EDIT THIS SECTION, INSTEAD RE-RUN doctoc TO UPDATE -->
- [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)
<!-- END doctoc generated TOC please keep comment here to allow auto update -->
# 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)
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