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 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

See Import instructions here: https://www.zotero.org/support/kb/importing_standardized_formats

Watch the 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 or reach out to me.

• 2048
• Accessibility
• Azul
• Blokus
• Carcassonne
• Diplomacy
• Dixit
• Dominion
• Frameworks
• Game Design
• General Gameplay
• Hanabi
• Hearthstone
• Hive
• Jenga
• Kingdomino
• Lost Cities
• Mafia
• Magic: The Gathering
• Mobile Games
• Modern Art: The card game
• Monopoly
• Monopoly Deal
• Netrunner
• Nmbr9
• Pandemic
• Patchwork
• Pentago
• Puerto Rico
• Quixo
• Race for the Galaxy
• Resistance: Avalon
• RISK
• Santorini
• Scotland Yard
• Secret Hitler
• Set
• Settlers of Catan
• Shobu
• Terra Mystica
• Terraforming Mars
• Tetris Link
• Ticket to Ride
• Ultimate Tic-Tac-Toe
• UNO
• Yahtzee
• Similar Projects
• License

• Systematic Selection of N-Tuple Networks for 2048 (bookSection)
• Systematic selection of N-tuple networks with consideration of interinfluence for game 2048 (conferencePaper)
• An investigation into 2048 AI strategies (conferencePaper)
• Threes!, Fives, 1024!, and 2048 are Hard (journalArticle)
• Making Change in 2048 (journalArticle)
• Analysis of the Game "2048" and its Generalization in Higher Dimensions (journalArticle)
• Multi-Stage Temporal Difference Learning for 2048-like Games (journalArticle)
• 2048 is (PSPACE) Hard, but Sometimes Easy (journalArticle)
• Temporal difference learning of N-tuple networks for the game 2048 (conferencePaper)
• On the Complexity of Slide-and-Merge Games (journalArticle)
• 2048 Without New Tiles Is Still Hard (journalArticle)

• Meeple Centred Design: A Heuristic Toolkit for Evaluating the Accessibility of Tabletop Games (journalArticle)
• Eighteen Months of Meeple Like Us: An Exploration into the State of Board Game Accessibility (journalArticle)

• A summary of a dissertation on Azul (report)
• Ceramic: A research environment based on the multi-player strategic board game Azul (conferencePaper)
• Ceramic: A research environment based on the multi-player strategic board game Azul (computerProgram)

• FPGA Blokus Duo Solver using a massively parallel architecture (conferencePaper)
• Blokus Duo game on FPGA (conferencePaper)
• Algorithm Modeling for Hardware Implementation of a Blokus Duo Player (thesis)
• Artificial Intelligence for Blokus Classic using Heuristics, FloodFill, and Greedy Algorithm (journalArticle)
• FPGA implementation of Blokus Duo player using hardware/software co-design (conferencePaper)
• Exploring Combinatorics and Graph Theory with Simple Blokus (journalArticle)
• An FPGA-based specific processor for Blokus Duo (conferencePaper)
• Blokus Game Solver (report)
• Highly scalable, shared-memory, Monte-Carlo tree search based Blokus Duo Solver on FPGA (conferencePaper)
• Implementation of a highly scalable blokus duo solver on FPGA (conferencePaper)
• An implementation of Blokus Duo player on FPGA (conferencePaper)
• The Liquid Metal Blokus Duo Design (conferencePaper)
• Artificial intelligence of Blokus Duo on FPGA using Cyber Work Bench (conferencePaper)
• Hardware/software co-design architecture for Blokus Duo solver (conferencePaper)
• From C to Blokus Duo with LegUp high-level synthesis (conferencePaper)
• Blokus Duo engine on a Zynq (conferencePaper)
• Optimize MinMax algorithm to solve Blokus Duo game by HDL (conferencePaper)
• A Case Study of FPGA Blokus Duo Solver by System-Level Design (journalArticle)

• Playing Carcassonne with Monte Carlo Tree Search (journalArticle)
• On the Evolution of the MCTS Upper Confidence Bounds for Trees by Means of Evolutionary Algorithms in the Game of Carcassonne (journalArticle)
• Evolving the MCTS Upper Confidence Bounds for Trees Using a Semantic-inspired Evolutionary Algorithm in the Game of Carcassonne (preprint)

• Learning to Play No-Press Diplomacy with Best Response Policy Iteration (journalArticle)
• No Press Diplomacy: Modeling Multi-Agent Gameplay (journalArticle)
• Agent Madoff: A Heuristic-Based Negotiation Agent For The Diplomacy Strategy Game (journalArticle)
• Monte Carlo Tree Search for the Game of Diplomacy (conferencePaper)
• Human-Level Performance in No-Press Diplomacy via Equilibrium Search (journalArticle)

• Creative Captioning: An AI Grand Challenge Based on the Dixit Board Game (journalArticle)
• Dixit: Interactive Visual Storytelling via Term Manipulation (journalArticle)

• Dominion Simulator (computerProgram)
• Dominion Simulator Source Code (computerProgram)
• Best and worst openings in Dominion (blogPost)
• Optimal Card Ratios in Dominion (blogPost)
• Card Winning Stats on Dominion Server (blogPost)
• Dominion Strategy Forum (forumPost)
• Clustering Player Strategies from Variable-Length Game Logs in Dominion (journalArticle)
• Game Balancing in Dominion: An Approach to Identifying Problematic Game Elements (journalArticle)

• RLCard: A Toolkit for Reinforcement Learning in Card Games (journalArticle)
• Design and Implementation of TAG: A Tabletop Games Framework (journalArticle)
• Game Tree Search Algorithms - C++ library for AI bot programming. (computerProgram)
• TAG: Tabletop Games Framework (computerProgram)

• MDA: A Formal Approach to Game Design and Game Research (conferencePaper)
• Exploring anonymity in cooperative board games (conferencePaper)

• Player of Games (journalArticle)
• A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play (journalArticle)

• How to Make the Perfect Fireworks Display: Two Strategies forHanabi (journalArticle)
• Evaluating and modelling Hanabi-playing agents (conferencePaper)
• The Hanabi challenge: A new frontier for AI research (journalArticle)
• The 2018 Hanabi competition (conferencePaper)
• Diverse Agents for Ad-Hoc Cooperation in Hanabi (conferencePaper)
• Improving Policies via Search in Cooperative Partially Observable Games (journalArticle)
• Hanabi is NP-hard, Even for Cheaters who Look at Their Cards (journalArticle)
• Generating and Adapting to Diverse Ad-Hoc Cooperation Agents in Hanabi (journalArticle)
• Evaluating the Rainbow DQN Agent in Hanabi with Unseen Partners (journalArticle)
• Re-determinizing MCTS in Hanabi (conferencePaper)
• Evolving Agents for the Hanabi 2018 CIG Competition (conferencePaper)
• Aspects of the Cooperative Card Game Hanabi (bookSection)
• Playing Hanabi Near-Optimally (bookSection)
• An intentional AI for hanabi (conferencePaper)
• Solving Hanabi: Estimating Hands by Opponent's Actions in Cooperative Game with Incomplete Information (conferencePaper)
• A Browser-based Interface for the Exploration and Evaluation of Hanabi AIs (journalArticle)
• I see what you see: Integrating eye tracking into Hanabi playing agents (journalArticle)
• State of the art Hanabi bots + simulation framework in rust (computerProgram)
• A strategy simulator for the well-known cooperative card game Hanabi (computerProgram)
• A framework for writing bots that play Hanabi (computerProgram)
• Operationalizing Intentionality to Play Hanabi with Human Players (journalArticle)
• Behavioral Evaluation of Hanabi Rainbow DQN Agents and Rule-Based Agents (journalArticle)
• Playing mini-Hanabi card game with Q-learning (conferencePaper)
• Hanabi Open Agent Dataset (computerProgram)
• Hanabi Open Agent Dataset (conferencePaper)
• Evaluation of Human-AI Teams for Learned and Rule-Based Agents in Hanabi (journalArticle)
• Emergence of Cooperative Impression With Self-Estimation, Thinking Time, and Concordance of Risk Sensitivity in Playing Hanabi (journalArticle)
• K-level Reasoning for Zero-Shot Coordination in Hanabi (conferencePaper)
• Is Vanilla Policy Gradient Overlooked? Analyzing Deep Reinforcement Learning for Hanabi (journalArticle)
• Generating and Adapting to Diverse Ad-Hoc Partners in Hanabi (journalArticle)
• Theory of Mind for Multi-agent Coordination in Hanabi (thesis)
• The Hanabi challenge: From Artificial Teams to Mixed Human-Machine Teams (thesis)
• A Graphical User Interface For The Hanabi Challenge Benchmark (thesis)
• Analysis of Symmetry and Conventions in Off-Belief Learning (OBL) in Hanabi (blogPost)
• Using intuitive behavior models to adapt to and work with human teammates in Hanabi (thesis)
• Behavioral Differences is the Key of Ad-hoc Team Cooperation in Multiplayer Games Hanabi (preprint)
• The Hidden Rules of Hanabi: How Humans Outperform AI Agents (conferencePaper)

• Mapping Hearthstone Deck Spaces through MAP-Elites with Sliding Boundaries (journalArticle)
• Multiplayer Tension In the Wild: A Hearthstone Case (conferencePaper)
• Improving Hearthstone AI by Combining MCTS and Supervised Learning Algorithms (preprint)
• Analysis of gameplay strategies in hearthstone: a data science approach (thesis)
• Decision-Making in Hearthstone Based on Evolutionary Algorithm (journalArticle)
• I am a legend: Hacking hearthstone using statistical learning methods (conferencePaper)
• The Many AI Challenges of Hearthstone (journalArticle)
• Evolutionary deckbuilding in hearthstone (conferencePaper)
• Evolving the Hearthstone Meta (preprint)
• Optimizing Hearthstone agents using an evolutionary algorithm (journalArticle)
• Exploring the hearthstone deck space (conferencePaper)
• Computational Intelligence Techniques for Games with Incomplete Information (thesis)
• Perfect Information Hearthstone is PSPACE-hard (preprint)
• Summarizing Strategy Card Game AI Competition (preprint)
• Towards sample efficient deep reinforcement learning in collectible card games (journalArticle)

• On the complexity of Hive (thesis)
• The Cost of Reinforcement Learning for Game Engines: The AZ-Hive Case-study (conferencePaper)

• Jidoukan Jenga: Teaching English through remixing games and game rules (journalArticle)
• Maximum genus of the Jenga like configurations (journalArticle)
• Deep Instance Segmentation and Visual Servoing to Play Jenga with a Cost-Effective Robotic System (journalArticle)

• Monte Carlo Methods for the Game Kingdomino (conferencePaper)
• Monte Carlo Methods for the Game Kingdomino (journalArticle)
• NP-completeness of the game Kingdomino (journalArticle)

• Applying Neural Networks and Genetic Programming to the Game Lost Cities (conferencePaper)

• A mathematical model of the Mafia game (journalArticle)
• Automatic Long-Term Deception Detection in Group Interaction Videos (journalArticle)
• Human-Side Strategies in the Werewolf Game Against the Stealth Werewolf Strategy (bookSection)
• A Theoretical Study of Mafia Games (journalArticle)

• Ensemble Determinization in Monte Carlo Tree Search for the Imperfect Information Card Game Magic: The Gathering (journalArticle)
• Optimal Card-Collecting Strategies for Magic: The Gathering (journalArticle)
• Monte Carlo search applied to card selection in Magic: The Gathering (conferencePaper)
• Magic: the Gathering is as Hard as Arithmetic (journalArticle)
• Magic: The Gathering is Turing Complete (journalArticle)
• Neural Networks Models for Analyzing Magic: the Gathering Cards (journalArticle)
• Neural Networks Models for Analyzing Magic: The Gathering Cards (bookSection)
• The Complexity of Deciding Legality of a Single Step of Magic: The Gathering (conferencePaper)
• Magic: The Gathering in Common Lisp (conferencePaper)
• Magic: The Gathering in Common Lisp (computerProgram)
• Mathematical programming and Magic: The Gathering (thesis)
• Deck Construction Strategies for Magic: The Gathering (conferencePaper)
• Deckbuilding in Magic: The Gathering Using a Genetic Algorithm (thesis)
• Magic: The Gathering Deck Performance Prediction (report)
• AI solutions for drafting in Magic: the Gathering (journalArticle)

• Trainyard is NP-Hard (journalArticle)
• Threes!, Fives, 1024!, and 2048 are Hard (journalArticle)
• Rikudo is NP-complete (journalArticle)

• A constraint programming based solver for Modern Art (computerProgram)

• Monopoly as a Markov Process (journalArticle)
• Learning Monopoly Gameplay: A Hybrid Model-Free Deep Reinforcement Learning and Imitation Learning Approach (journalArticle)
• Negotiation strategy of agents in the MONOPOLY game (conferencePaper)
• Generating interesting Monopoly boards from open data (conferencePaper)
• Estimating the probability that the game of Monopoly never ends (conferencePaper)
• Learning to Play Monopoly with Monte Carlo Tree Search (report)
• Monopoly Using Reinforcement Learning (conferencePaper)
• A Markovian Exploration of Monopoly (report)
• Learning to play Monopoly: A Reinforcement Learning approach (conferencePaper)
• What’s the Best Monopoly Strategy? (presentation)

• Implementation of Artificial Intelligence with 3 Different Characters of AI Player on “Monopoly Deal” Computer Game (bookSection)

• Netrunner Mate-in-1 or -2 is Weakly NP-Hard (journalArticle)

• Nmbr9 as a Constraint Programming Challenge (journalArticle)
• Nmbr9 as a Constraint Programming Challenge (blogPost)

• NP-Completeness of Pandemic (journalArticle)

• State Representation and Polyomino Placement for the Game Patchwork (blogPost)
• State Representation and Polyomino Placement for the Game Patchwork (journalArticle)
• State Representation and Polyomino Placement for the Game Patchwork (presentation)

• On Solving Pentago (thesis)
• Pentago is a First Player Win: Strongly Solving a Game Using Parallel In-Core Retrograde Analysis (journalArticle)
• A massively parallel pentago solver (computerProgram)
• An interactive explorer for perfect pentago play (computerProgram)
• An Application of Machine Learning to the Board Game Pentago (report)
• Learning finite functions by neural networks : Evaluation of Pentago positions by convolutional neural networks (report)

• Artificial Intelligence Techniques for the Puerto Rico Strategy Game (bookSection)

• QUIXO is EXPTIME-complete (journalArticle)
• Quixo Is Solved (journalArticle)

• SCOUT: A Case-Based Reasoning Agent for Playing Race for the Galaxy (bookSection)
• Ludometrics: Luck, and How to Measure It (journalArticle)

• Finding Friend and Foe in Multi-Agent Games (journalArticle)

• Mini-Risk: Strategies for a Simplified Board Game (journalArticle)
• Learning the risk board game with classifier systems (conferencePaper)
• Markov Chains and the RISK Board Game (journalArticle)
• Markov Chains for the RISK Board Game Revisited (journalArticle)
• Planning an Endgame Move Set for the Game RISK: A Comparison of Search Algorithms (journalArticle)
• An Intelligent Artificial Player for the Game of Risk (presentation)
• RISKy Business: An In-Depth Look at the Game RISK (journalArticle)
• RISK Board Game ‐ Battle Outcome Analysis (journalArticle)
• A multi-agent system for playing the board game risk (thesis)
• Monte Carlo Tree Search for Risk (conferencePaper)
• Wargaming with Monte-Carlo Tree Search (presentation)

• A Mathematical Analysis of the Game of Santorini (thesis)
• A Mathematical Analysis of the Game of Santorini (computerProgram)

• The complexity of Scotland Yard (report)

• Competing in a Complex Hidden Role Game with Information Set Monte Carlo Tree Search (journalArticle)

• Game, Set, Math (journalArticle)
• The Joy of SET (journalArticle)

• The effectiveness of persuasion in The Settlers of Catan (conferencePaper)
• Avoiding Revenge Using Optimal Opponent Ranking Strategy in the Board Game Catan (journalArticle)
• Game strategies for The Settlers of Catan (conferencePaper)
• Monte-Carlo Tree Search in Settlers of Catan (bookSection)
• Deep Reinforcement Learning in Strategic Board Game Environments (bookSection)
• Settlers of Catan bot trained using reinforcement learning (computerProgram)
• Trading in a multiplayer board game: Towards an analysis of non-cooperative dialogue (conferencePaper)
• POMCP with Human Preferencesin Settlers of Catan (journalArticle)
• The impact of loaded dice in Catan (blogPost)
• Monte Carlo Tree Search in a Modern Board Game Framework (journalArticle)
• Reinforcement Learning of Strategies for Settlers of Catan (conferencePaper)
• Playing Catan with Cross-dimensional Neural Network (journalArticle)
• Strategic Dialogue Management via Deep Reinforcement Learning (journalArticle)
• Analysis of 'The Settlers of Catan' Using Markov Chains (thesis)
• Learning to Play Settlers of Catan with Deep Reinforcement Learning (blogPost)
• Using Ant Colony Optimisation for map generation and improving game balance in the Terra Mystica and Settlers of Catan board games (conferencePaper)

• Shobu AI Playground (computerProgram)
• Shobu randomly played games dataset (webpage)

• Using Tabu Search Algorithm for Map Generation in the Terra Mystica Tabletop Game (conferencePaper)
• Mastering Terra Mystica: Applying Self-Play to Multi-agent Cooperative Board Games (journalArticle)
• TM AI: Play TM against AI players. (computerProgram)
• Using Ant Colony Optimisation for map generation and improving game balance in the Terra Mystica and Settlers of Catan board games (conferencePaper)
• Map Generation and Balance in the Terra Mystica Board Game Using Particle Swarm and Local Search (bookSection)
• Using Ant Colony Optimisation for map generation and improving game balance in the Terra Mystica and Settlers of Catan board games (conferencePaper)

• TAG: Terraforming Mars (journalArticle)

• A New Challenge: Approaching Tetris Link with AI (journalArticle)

• AI-based playtesting of contemporary board games (conferencePaper)
• Materials for Ticket to Ride Seattle and a framework for making more game boards (computerProgram)
• The Difficulty of Learning Ticket to Ride (report)
• Evolving maps and decks for ticket to ride (conferencePaper)
• Applications of Graph Theory and Probability in the Board Game Ticket to Ride (presentation)

• At Most 43 Moves, At Least 29: Optimal Strategies and Bounds for Ultimate Tic-Tac-Toe (journalArticle)

• UNO Is Hard, Even for a Single Player (bookSection)
• The complexity of UNO (journalArticle)

• Nearly Optimal Computer Play in Multi-player Yahtzee (bookSection)
• Computer Strategies for Solitaire Yahtzee (conferencePaper)
• Modeling expert problem solving in a game of chance: a Yahtzeec case study (journalArticle)
• Probabilites In Yahtzee (journalArticle)
• Optimal Solitaire Yahtzee Strategies (presentation)
• Yahtzee: a Large Stochastic Environment for RL Benchmarks (journalArticle)
• Optimal Yahtzee performance in multi-player games (thesis)
• How to Maximize Your Score in Solitaire Yahtzee (manuscript)
• Using Deep Q-Learning to Compare Strategy Ladders of Yahtzee (thesis)
• Defensive Yahtzee (report)
• An Optimal Strategy for Yahtzee (report)
• Let’s Get Rolling! Exact Optimal Solitaire Yahtzee (journalArticle)

• https://github.com/benedekrozemberczki/awesome-monte-carlo-tree-search-papers

Creative Commons Zero v1.0 Universal. See LICENSE file for complete text.