boardgame-research/README.md
Nemo f5397c0648 New Paper on Hanabi\n
Behavioral Differences is the Key of Ad-hoc Team Cooperation in Multiplayer Games Hanabi
https://arxiv.org/abs/2303.06775
2023-03-16 12:27:37 +05:30

364 lines
28 KiB
Markdown
Raw Blame History

This file contains ambiguous Unicode characters

This file contains Unicode characters that might be confused with other characters. If you think that this is intentional, you can safely ignore this warning. Use the Escape button to reveal them.

# 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 related research papers, code, blog posts, and other media. The list primarily includes research on "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.
You can browse the collection at <https://www.zotero.org/captn3m0/collections/8S9AI4TI> as well.
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 -->
- [2048](#2048)
- [Accessibility](#accessibility)
- [Azul](#azul)
- [Blokus](#blokus)
- [Carcassonne](#carcassonne)
- [Diplomacy](#diplomacy)
- [Dixit](#dixit)
- [Dominion](#dominion)
- [Frameworks](#frameworks)
- [Game Design](#game-design)
- [General Gameplay](#general-gameplay)
- [Hanabi](#hanabi)
- [Hearthstone](#hearthstone)
- [Hive](#hive)
- [Jenga](#jenga)
- [Kingdomino](#kingdomino)
- [Lost Cities](#lost-cities)
- [Mafia](#mafia)
- [Magic: The Gathering](#magic-the-gathering)
- [Mobile Games](#mobile-games)
- [Modern Art: The card game](#modern-art-the-card-game)
- [Monopoly](#monopoly)
- [Monopoly Deal](#monopoly-deal)
- [Netrunner](#netrunner)
- [Nmbr9](#nmbr9)
- [Pandemic](#pandemic)
- [Patchwork](#patchwork)
- [Pentago](#pentago)
- [Quixo](#quixo)
- [Race for the Galaxy](#race-for-the-galaxy)
- [Resistance: Avalon](#resistance-avalon)
- [RISK](#risk)
- [Santorini](#santorini)
- [Scotland Yard](#scotland-yard)
- [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)
- [Similar Projects](#similar-projects)
- [License](#license)
<!-- END doctoc generated TOC please keep comment here to allow auto update -->
# 2048
- [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)
- [Temporal difference learning of N-tuple networks for the game 2048](http://ieeexplore.ieee.org/document/6932907/) (conferencePaper)
- [On the Complexity of Slide-and-Merge Games](http://arxiv.org/abs/1501.03837) (journalArticle)
- [2048 Without New Tiles Is Still Hard](http://drops.dagstuhl.de/opus/volltexte/2016/5885/) (journalArticle)
# 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)
# Azul
- [A summary of a dissertation on Azul](https://old.reddit.com/r/boardgames/comments/hxodaf/update_i_wrote_my_dissertation_on_azul/) (report)
- [Ceramic: A research environment based on the multi-player strategic board game Azul](https://ipsj.ixsq.nii.ac.jp/ej/?action=repository_action_common_download&item_id=207669&item_no=1&attribute_id=1&file_no=1) (conferencePaper)
- [Ceramic: A research environment based on the multi-player strategic board game Azul](https://github.com/Swynfel/ceramic) (computerProgram)
# Blokus
- [Blokus Game Solver](https://digitalcommons.calpoly.edu/cpesp/290/) (report)
- [FPGA Blokus Duo Solver using a massively parallel architecture](http://ieeexplore.ieee.org/document/6718426/) (conferencePaper)
- [Blokus Duo game on FPGA](http://ieeexplore.ieee.org/document/6714256/) (conferencePaper)
# Carcassonne
- [Playing Carcassonne with Monte Carlo Tree Search](http://arxiv.org/abs/2009.12974) (journalArticle)
- [On the Evolution of the MCTS Upper Confidence Bounds for Trees by Means of Evolutionary Algorithms in the Game of Carcassonne](http://arxiv.org/abs/2112.09697) (journalArticle)
- [Evolving the MCTS Upper Confidence Bounds for Trees Using a Semantic-inspired Evolutionary Algorithm in the Game of Carcassonne](http://arxiv.org/abs/2208.13589) (preprint)
# 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)
- [Human-Level Performance in No-Press Diplomacy via Equilibrium Search](http://arxiv.org/abs/2010.02923) (journalArticle)
# Dixit
- [Creative Captioning: An AI Grand Challenge Based on the Dixit Board Game](http://arxiv.org/abs/2010.00048) (journalArticle)
- [Dixit: Interactive Visual Storytelling via Term Manipulation](http://arxiv.org/abs/1903.02230) (journalArticle)
# Dominion
- [Dominion Simulator](https://dominionsimulator.wordpress.com/f-a-q/) (computerProgram)
- [Dominion Simulator Source Code](https://github.com/mikemccllstr/dominionstats/) (computerProgram)
- [Best and worst openings in Dominion](http://councilroom.com/openings) (blogPost)
- [Optimal Card Ratios in Dominion](http://councilroom.com/optimal_card_ratios) (blogPost)
- [Card Winning Stats on Dominion Server](http://councilroom.com/supply_win) (blogPost)
- [Dominion Strategy Forum](http://forum.dominionstrategy.com/index.php) (forumPost)
- [Clustering Player Strategies from Variable-Length Game Logs in Dominion](http://arxiv.org/abs/1811.11273) (journalArticle)
- [Game Balancing in Dominion: An Approach to Identifying Problematic Game Elements](http://cs.gettysburg.edu/~tneller/games/aiagd/papers/EAAI-00039-FordC.pdf) (journalArticle)
# Frameworks
- [RLCard: A Toolkit for Reinforcement Learning in Card Games](http://arxiv.org/abs/1910.04376) (journalArticle)
- [Design and Implementation of TAG: A Tabletop Games Framework](http://arxiv.org/abs/2009.12065) (journalArticle)
- [Game Tree Search Algorithms - C++ library for AI bot programming.](https://github.com/AdamStelmaszczyk/gtsa) (computerProgram)
- [TAG: Tabletop Games Framework](https://github.com/GAIGResearch/TabletopGames) (computerProgram)
# Game Design
- [MDA: A Formal Approach to Game Design and Game Research](https://aaai.org/Library/Workshops/2004/ws04-04-001.php) (conferencePaper)
- [Exploring anonymity in cooperative board games](http://www.digra.org/digital-library/publications/exploring-anonymity-in-cooperative-board-games/) (conferencePaper)
# General Gameplay
- [Player of Games](http://arxiv.org/abs/2112.03178) (journalArticle)
- [A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play](https://www.science.org/doi/10.1126/science.aar6404) (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)
- [Hanabi Open Agent Dataset](https://github.com/aronsar/hoad) (computerProgram)
- [Hanabi Open Agent Dataset](https://dl.acm.org/doi/10.5555/3463952.3464188) (conferencePaper)
- [Evaluation of Human-AI Teams for Learned and Rule-Based Agents in Hanabi](https://arxiv.org/abs/2107.07630) (journalArticle)
- [Emergence of Cooperative Impression With Self-Estimation, Thinking Time, and Concordance of Risk Sensitivity in Playing Hanabi](https://www.frontiersin.org/articles/10.3389/frobt.2021.658348/full) (journalArticle)
- [K-level Reasoning for Zero-Shot Coordination in Hanabi](https://papers.neurips.cc/paper/2021/hash/4547dff5fd7604f18c8ee32cf3da41d7-Abstract.html) (conferencePaper)
- [Is Vanilla Policy Gradient Overlooked? Analyzing Deep Reinforcement Learning for Hanabi](http://arxiv.org/abs/2203.11656) (journalArticle)
- [Generating and Adapting to Diverse Ad-Hoc Partners in Hanabi](https://ieeexplore.ieee.org/document/9762901/) (journalArticle)
- [Theory of Mind for Multi-agent Coordination in Hanabi](http://fse.studenttheses.ub.rug.nl/id/eprint/28327) (thesis)
- [The Hanabi challenge: From Artificial Teams to Mixed Human-Machine Teams](http://oru.diva-portal.org/smash/record.jsf?pid=diva2%3A1691114&dswid=-1981) (thesis)
- [A Graphical User Interface For The Hanabi Challenge Benchmark](http://urn.kb.se/resolve?urn=urn:nbn:se:oru:diva-94615) (thesis)
- [Analysis of Symmetry and Conventions in Off-Belief Learning (OBL) in Hanabi](https://fanpu.io/blog/2022/symmetry-and-conventions-in-obl-hanabi/) (blogPost)
- [Using intuitive behavior models to adapt to and work with human teammates in Hanabi](http://reports-archive.adm.cs.cmu.edu/anon/anon/usr0/ftp/usr/ftp/2022/abstracts/22-119.html) (thesis)
- [Behavioral Differences is the Key of Ad-hoc Team Cooperation in Multiplayer Games Hanabi](http://arxiv.org/abs/2303.06775) (preprint)
# Hearthstone
- [Mapping Hearthstone Deck Spaces through MAP-Elites with Sliding Boundaries](http://arxiv.org/abs/1904.10656) (journalArticle)
# Hive
- [On the complexity of Hive](https://dspace.library.uu.nl/handle/1874/396955) (thesis)
- [The Cost of Reinforcement Learning for Game Engines: The AZ-Hive Case-study](https://dl.acm.org/doi/10.1145/3489525.3511685) (conferencePaper)
# Jenga
- [Jidoukan Jenga: Teaching English through remixing games and game rules](https://www.llpjournal.org/2020/04/13/jidokan-jenga.html) (journalArticle)
- [Maximum genus of the Jenga like configurations](http://arxiv.org/abs/1708.01503) (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)
# Lost Cities
- [Applying Neural Networks and Genetic Programming to the Game Lost Cities](https://minds.wisconsin.edu/bitstream/handle/1793/79080/LydeenSpr18.pdf?sequence=1&isAllowed=y) (conferencePaper)
# Mafia
- [A mathematical model of the Mafia game](http://arxiv.org/abs/1009.1031v3) (journalArticle)
- [Automatic Long-Term Deception Detection in Group Interaction Videos](http://arxiv.org/abs/1905.08617) (journalArticle)
- [Human-Side Strategies in the Werewolf Game Against the Stealth Werewolf Strategy](http://link.springer.com/10.1007/978-3-319-50935-8_9) (bookSection)
- [A Theoretical Study of Mafia Games](http://arxiv.org/abs/0804.0071) (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)
- [Neural Networks Models for Analyzing Magic: The Gathering Cards](http://link.springer.com/10.1007/978-3-030-04179-3_20) (bookSection)
- [The Complexity of Deciding Legality of a Single Step of Magic: The Gathering](https://livrepository.liverpool.ac.uk/3029568/) (conferencePaper)
- [Magic: The Gathering in Common Lisp](https://vixra.org/abs/2001.0065) (conferencePaper)
- [Magic: The Gathering in Common Lisp](https://github.com/jeffythedragonslayer/maglisp) (computerProgram)
- [Mathematical programming and Magic: The Gathering](https://commons.lib.niu.edu/handle/10843/19194) (thesis)
- [Deck Construction Strategies for Magic: The Gathering](https://www.doi.org/10.1685/CSC06077) (conferencePaper)
- [Deckbuilding in Magic: The Gathering Using a Genetic Algorithm](https://doi.org/11250/2462429) (thesis)
- [Magic: The Gathering Deck Performance Prediction](http://cs229.stanford.edu/proj2012/HauPlotkinTran-MagicTheGatheringDeckPerformancePrediction.pdf) (report)
- [AI solutions for drafting in Magic: the Gathering](http://arxiv.org/abs/2009.00655) (journalArticle)
# Mobile Games
- [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)
- [Rikudo is NP-complete](https://linkinghub.elsevier.com/retrieve/pii/S0304397522000457) (journalArticle)
# Modern Art: The card game
- [A constraint programming based solver for Modern Art](https://github.com/captn3m0/modernart) (computerProgram)
# Monopoly
- [Monopoly as a Markov Process](https://doi.org/10.1080%2F0025570x.1972.11976187) (journalArticle)
- [Learning Monopoly Gameplay: A Hybrid Model-Free Deep Reinforcement Learning and Imitation Learning Approach](http://arxiv.org/abs/2103.00683) (journalArticle)
- [Negotiation strategy of agents in the MONOPOLY game](http://ieeexplore.ieee.org/document/1013210/) (conferencePaper)
- [Generating interesting Monopoly boards from open data](http://ieeexplore.ieee.org/document/6374168/) (conferencePaper)
- [Estimating the probability that the game of Monopoly never ends](http://ieeexplore.ieee.org/document/5429349/) (conferencePaper)
- [Learning to Play Monopoly with Monte Carlo Tree Search](https://project-archive.inf.ed.ac.uk/ug4/20181042/ug4_proj.pdf) (report)
- [Monopoly Using Reinforcement Learning](https://ieeexplore.ieee.org/document/8929523/) (conferencePaper)
- [A Markovian Exploration of Monopoly](https://pi4.math.illinois.edu/wp-content/uploads/2014/10/Gartland-Burson-Ferguson-Markovopoly.pdf) (report)
- [Learning to play Monopoly: A Reinforcement Learning approach](https://intelligence.csd.auth.gr/publication/conference-papers/learning-to-play-monopoly-a-reinforcement-learning-approach/) (conferencePaper)
- [Whats the Best Monopoly Strategy?](https://core.ac.uk/download/pdf/48614184.pdf) (presentation)
# 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)
# Netrunner
- [Netrunner Mate-in-1 or -2 is Weakly NP-Hard](http://arxiv.org/abs/1710.05121) (journalArticle)
# 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)
# Pandemic
- [NP-Completeness of Pandemic](https://www.jstage.jst.go.jp/article/ipsjjip/20/3/20_723/_article) (journalArticle)
# 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)
# Pentago
- [On Solving Pentago](http://www.ke.tu-darmstadt.de/lehre/arbeiten/bachelor/2011/Buescher_Niklas.pdf) (thesis)
- [Pentago is a First Player Win: Strongly Solving a Game Using Parallel In-Core Retrograde Analysis](http://arxiv.org/abs/1404.0743) (journalArticle)
- [A massively parallel pentago solver](https://github.com/girving/pentago) (computerProgram)
- [An interactive explorer for perfect pentago play](https://perfect-pentago.net/) (computerProgram)
# 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)
- [Ludometrics: Luck, and How to Measure It](http://arxiv.org/abs/1811.00673) (journalArticle)
# Resistance: Avalon
- [Finding Friend and Foe in Multi-Agent Games](http://arxiv.org/abs/1906.02330) (journalArticle)
# 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](http://urn.kb.se/resolve?urn=urn:nbn:se:bth-3781) (thesis)
- [Monte Carlo Tree Search for Risk](https://www.sto.nato.int/publications/STO%20Meeting%20Proceedings/STO-MP-SAS-OCS-ORA-2020/MP-SAS-OCS-ORA-2020-WCM-01.pdf) (conferencePaper)
- [Wargaming with Monte-Carlo Tree Search](https://www.sto.nato.int/publications/STO%20Meeting%20Proceedings/STO-MP-SAS-OCS-ORA-2020/MP-SAS-OCS-ORA-2020-WCM-01P.pdf) (presentation)
# Santorini
- [A Mathematical Analysis of the Game of Santorini](https://openworks.wooster.edu/independentstudy/8917/) (thesis)
- [A Mathematical Analysis of the Game of Santorini](https://github.com/carsongeissler/SantoriniIS) (computerProgram)
# Scotland Yard
- [The complexity of Scotland Yard](https://eprints.illc.uva.nl/id/eprint/193/1/PP-2006-18.text.pdf) (report)
# 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](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](https://escholarship.org/uc/item/9zt506xx) (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](https://www.researchgate.net/publication/228728063_Reinforcement_learning_of_strategies_for_Settlers_of_Catan) (conferencePaper)
- [Playing Catan with Cross-dimensional Neural Network](http://arxiv.org/abs/2008.07079) (journalArticle)
- [Strategic Dialogue Management via Deep Reinforcement Learning](http://arxiv.org/abs/1511.08099) (journalArticle)
- [Analysis of 'The Settlers of Catan' Using Markov Chains](https://repository.tcu.edu/handle/116099117/49062) (thesis)
- [Learning to Play Settlers of Catan with Deep Reinforcement Learning](https://settlers-rl.github.io/) (blogPost)
# 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)
- [Mastering Terra Mystica: Applying Self-Play to Multi-agent Cooperative Board Games](http://arxiv.org/abs/2102.10540) (journalArticle)
- [TM AI: Play TM against AI players.](https://lodev.org/tmai/) (computerProgram)
# 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)
- [The Difficulty of Learning Ticket to Ride](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 and Probability in the Board Game Ticket to Ride](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)
- [Probabilites In Yahtzee](https://pubs.nctm.org/view/journals/mt/75/9/article-p751.xml) (journalArticle)
- [Optimal Solitaire Yahtzee Strategies](http://www.yahtzee.org.uk/optimal_yahtzee_TV.pdf) (presentation)
- [Yahtzee: a Large Stochastic Environment for RL Benchmarks](http://researchers.lille.inria.fr/~lazaric/Webpage/PublicationsByTopic_files/bonarini2005yahtzee.pdf) (journalArticle)
- [Optimal Yahtzee performance in multi-player games](https://www.csc.kth.se/utbildning/kth/kurser/DD143X/dkand13/Group4Per/report/12-serra-widell-nigata.pdf) (thesis)
- [How to Maximize Your Score in Solitaire Yahtzee](http://www-set.win.tue.nl/~wstomv/misc/yahtzee/yahtzee-report-unfinished.pdf) (manuscript)
- [Using Deep Q-Learning to Compare Strategy Ladders of Yahtzee](https://raw.githubusercontent.com/philvasseur/Yahtzee-DQN-Thesis/dcf2bfe15c3b8c0ff3256f02dd3c0aabdbcbc9bb/webpage/final_report.pdf) (thesis)
- [Defensive Yahtzee](http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-168668) (report)
- [An Optimal Strategy for Yahtzee](http://www.cs.loyola.edu/~jglenn/research/optimal_yahtzee.pdf) (report)
# Similar Projects
- https://github.com/benedekrozemberczki/awesome-monte-carlo-tree-search-papers
# License
Creative Commons Zero v1.0 Universal. See LICENSE file for complete text.