List of Modern Boardgame Research

boardgame-research

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 instead. The list also covers some computer-games that fall under similar themes.

If you aren't able to access any paper on this list, please try using Sci-Hub or reach out to me .

Table of Contents generated with DocToc

Settlers of Catan

• The effectiveness of persuasion in The Settlers of Catan
• Avoiding Revenge Using Optimal Opponent Ranking Strategy in the Board Game Catan
• Game strategies for The Settlers of Catan
• Monte-Carlo Tree Search in Settlers of Catan
• Settlers of Catan bot trained using reinforcement learning (MATLAB).
• Trading in a multiplayer board game:Towards an analysis of non-cooperative dialogue
• POMCP with Human Preferencesin Settlers of Catan
• Reinforcement Learning of Strategies for Settlers of Catan
• Deep Reinforcement Learning in Strategic Board GameEnvironments [ pdf ]
• Monte Carlo Tree Search in a Modern Board Game Framework

Diplomacy

• Learning to Play No-Press Diplomacy with Best Response Policy Iteration
• No Press Diplomacy: Modeling Multi-Agent Gameplay
• Agent Madoff: A Heuristic-Based Negotiation Agent For The Diplomacy Strategy Game

Risk

• Mini-Risk: Strategies for a Simplified Board Game
• A Multi-Agent System for playing theboard game Risk
• Learning the risk board game with classifier systems
• Markov Chains and the RISK Board Game
• Markov Chains for the RISK Board Game Revisited
• RISK Board Game ‐ Battle Outcome Analysis
• Planning an endgame move set for the game RISK
• RISKy Business: An In-Depth Look at the Game RISK
• An Intelligent Artificial Player for the Game of Risk

Kingdomino

• Monte Carlo Methods for the Game Kingdomino [ arXiv ]
• NP-completeness of the game Kingdomino

Patchwork

• State Representation and Polyomino Placement for the Game Patchwork

Nmbr9

• Nmbr9 as a Constraint Programming Challenge

Hanabi

• Re-determinizing MCTS in Hanabi
• Hanabi is NP-hard, Even for Cheaters who Look at Their Cards
• Evolving Agents for the Hanabi 2018 CIG Competition
• Aspects of the Cooperative Card Game Hanabi
• How to Make the Perfect Fireworks Display: Two Strategies for Hanabi
• Playing Hanabi Near-Optimally
• Evaluating and modelling Hanabi-playing agents
• An intentional AI for hanabi
• The Hanabi challenge: A new frontier for AI research [ arXiv ]] (DeepMind)
• Solving Hanabi: Estimating Hands by Opponent's Actions in Cooperative Game with Incomplete Information
• A Browser-based Interface for the Exploration and Evaluation of Hanabi AIs
• I see what you see: Integrating eye tracking into Hanabi playing agents
• The 2018 Hanabi competition
• Diverse Agents for Ad-Hoc Cooperation in Hanabi [ arXiv ]
• State of the art Hanabi bots + simulation framework in rust
• Improving Policies via Search in Cooperative Partially Observable Games (FB) [ code ]
• A strategy simulator for the well-known cooperative card game Hanabi
• A framework for writing bots that play Hanabi
• Evaluating the Rainbow DQN Agent in Hanabi with Unseen Partners

Race for the galaxy

• SCOUT: A Case-Based Reasoning Agent for Playing Race for the Galaxy

Monopoly

• Negotiation strategy of agents in the MONOPOLY game
• Generating interesting Monopoly boards from open data
• Estimating the probability that the game of Monopoly never ends
• Learning to play Monopoly:A Reinforcement Learning approach
• Monopoly as a Markov Process
• Learning to Play Monopoly withMonte Carlo Tree Search
• Monopoly Using Reinforcement Learning
• A Markovian Exploration of Monopoly
• What's the best Monopoly strategy

Magic: the Gathering

• Magic: the Gathering is as Hard as Arithmetic
• Magic: The Gathering is Turing Complete
• Neural Networks Models for Analyzing Magic: the Gathering Cards [ arXiv ]
• The Complexity of Deciding Legality of a Single Step of Magic: the Gathering
• Ensemble Determinization in Monte Carlo Tree Search for the Imperfect Information Card Game Magic: The Gathering
• Magic: The Gathering in Common Lisp [ source ]
• Deck Costruction Strategies for Magic: the Gathering
• Deckbuilding in Magic: The Gathering Using a Genetic Algorithm
• Mathematical programming and Magic: The Gathering®
• Optimal Card-Collecting Strategies for Magic: The Gathering
• Monte Carlo search applied to card selection in Magic: The Gathering
• Magic: The Gathering Deck Performance Prediction

Terra Mystica

• Using Tabu Search Algorithm for Map Generation in the Terra Mystica Tabletop Game

Mafia

• A mathematical model of the Mafia game
• Automatic Long-Term Deception Detection in Group Interaction Videos

The Resistance: Avalon

• Finding Friend and Foe in Multi-Agent Games

Ticket to Ride

• Evolving maps and decks for ticket to ride
• Materials for Ticket to Ride Seattle and a framework for making more game boards
• Applications of Graph Theory andProbability in the Board GameTicket toRide
• The Difficulty of Learning Ticket to Ride

Lost Cities

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

Uno

• The complexity of UNO
• UNO Is Hard, Even for a Single Player

Dominion

There is a simulator and the code behind the Dominion server running councilroom.com is available. councilroom has the best and worst openings , optimal card ratios , Card winning stats and lots of other empirical research.

• Clustering Player Strategies from Variable-Length Game Logs in Dominion

Quixo

• QUIXO is EXPTIME-complete

Mobile Games

• Trainyard is NP-Hard
• Threes!, Fives, 1024!, and 2048 are Hard

Race for the Galaxy

• SCOUT: A Case-Based Reasoning Agent for Playing Race for the Galaxy

Santorini

• A Mathematical Analysis of the Game of Santorini

Set

Set has a long history of mathematical research, so this list isn't exhaustive.

• Game, Set, Math
• The Joy of SET

Pentago

• On Solving Pentago

Blokus

• Blokus Game Solver

Monopoly Deal

• Implementation of AI Player on "Monopoly Deal"

Yahtzee

• Optimal Solitaire Yahtzee Strategies
• Nearly Optimal Computer Play in Multi-player Yahtzee
• Computer Strategies for Solitaire Yahtzee
• An optimal strategy for Yahtzee
• Yahtzee: a Large Stochastic Environment for RL Benchmarks
• Modeling expert problem solving in a game of chance: a Yahtzee case study
• Probabilites In Yahtzee
• Optimal Yahtzee performance in multi-player games
• Defensive Yahtzee
• Using Deep Q-Learning to Compare Strategy Ladders of Yahtzee
• How to Maximize Your Score in Solitaire Yahtzee

2048

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

Game Design

• MDA: A Formal Approach to Game Design and Game Research
• Exploring Anonymity in Cooperative Board Games

Frameworks/Toolkits

• RLCard: A Toolkit for Reinforcement Learning in Card Games