From 4bd72fe23d408251156155ee6bff4e1fe7163de7 Mon Sep 17 00:00:00 2001 From: Nemo Date: Tue, 28 Jul 2020 14:27:33 +0530 Subject: [PATCH] Sort games alphabetically --- README.md | 201 +++++++++++++++++++++++++++--------------------------- 1 file changed, 100 insertions(+), 101 deletions(-) diff --git a/README.md b/README.md index 90df1fa..5429c04 100644 --- a/README.md +++ b/README.md @@ -20,33 +20,33 @@ If you aren't able to access any paper on this list, please [try using Sci-Hub]( **Table of Contents** *generated with [DocToc](https://github.com/thlorenz/doctoc)* -- [Settlers of Catan](#settlers-of-catan) -- [Modern Art: The card game](#modern-art-the-card-game) -- [Diplomacy](#diplomacy) -- [Risk](#risk) -- [Kingdomino](#kingdomino) -- [Patchwork](#patchwork) -- [Nmbr9](#nmbr9) -- [Hanabi](#hanabi) - [Azul](#azul) -- [Monopoly](#monopoly) -- [Magic: the Gathering](#magic-the-gathering) -- [Terra Mystica](#terra-mystica) -- [Mafia](#mafia) -- [The Resistance: Avalon](#the-resistance-avalon) -- [Ticket to Ride](#ticket-to-ride) -- [Lost Cities](#lost-cities) -- [Uno](#uno) +- [Blokus](#blokus) +- [Diplomacy](#diplomacy) - [Dominion](#dominion) +- [Hanabi](#hanabi) +- [Settlers of Catan](#settlers-of-catan) +- [Kingdomino](#kingdomino) +- [Lost Cities](#lost-cities) +- [Mafia](#mafia) +- [Magic: the Gathering](#magic-the-gathering) +- [Modern Art: The card game](#modern-art-the-card-game) +- [Monopoly](#monopoly) +- [Monopoly Deal](#monopoly-deal) +- [Nmbr9](#nmbr9) +- [Pandemic](#pandemic) +- [Patchwork](#patchwork) +- [Pentago](#pentago) - [Quixo](#quixo) - [Race for the Galaxy](#race-for-the-galaxy) +- [The Resistance: Avalon](#the-resistance-avalon) +- [Risk](#risk) - [Santorini](#santorini) -- [Set](#set) -- [Pentago](#pentago) -- [Blokus](#blokus) -- [Pandemic](#pandemic) - [Scotland Yard](#scotland-yard) -- [Monopoly Deal](#monopoly-deal) +- [Set](#set) +- [Terra Mystica](#terra-mystica) +- [Ticket to Ride](#ticket-to-ride) +- [Uno](#uno) - [Yahtzee](#yahtzee) - [Mobile Games](#mobile-games) - [2048](#2048) @@ -55,47 +55,23 @@ If you aren't able to access any paper on this list, please [try using Sci-Hub]( -# Settlers of Catan -- [The effectiveness of persuasion in The Settlers of Catan ](https://doi.org/10.1109/CIG.2014.6932861) -- [Avoiding Revenge Using Optimal Opponent Ranking Strategy in the Board Game Catan ](https://doi.org/10.4018/IJGCMS.2018040103) -- [Game strategies for The Settlers of Catan](https://doi.org/10.1109/CIG.2014.6932884) -- [Monte-Carlo Tree Search in Settlers of Catan](https://doi.org/10.1007/978-3-642-12993-3_3) -- [Settlers of Catan bot trained using reinforcement learning (MATLAB).](https://jonzia.github.io/Catan/) -- [Trading in a multiplayer board game: Towards an analysis of non-cooperative dialogue](https://escholarship.org/content/qt9zt506xx/qt9zt506xx.pdf) -- [POMCP with Human Preferencesin Settlers of Catan](https://www.aaai.org/ocs/index.php/AIIDE/AIIDE18/paper/viewFile/18091/17217) -- [Reinforcement Learning of Strategies for Settlers of Catan](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.561.6293&rep=rep1&type=pdf) -- [Deep Reinforcement Learning in Strategic Board GameEnvironments](https://doi.org/10.1007/978-3-030-14174-5_16) [[pdf](https://hal.archives-ouvertes.fr/hal-02124411/document)] -- [Monte Carlo Tree Search in a Modern Board Game Framework](https://project.dke.maastrichtuniversity.nl/games/files/bsc/Roelofs_Bsc-paper.pdf) -- [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) +# Azul +- [A summary of a dissertation on Azul](https://old.reddit.com/r/boardgames/comments/hxodaf/update_i_wrote_my_dissertation_on_azul/fzd3961/?context=3) (unpublished) -# Modern Art: The card game -- [A constraint programming based solver for Modern Art](https://github.com/captn3m0/modernart) +# Blokus +- [Blokus Game Solver](https://digitalcommons.calpoly.edu/cpesp/290/) # Diplomacy - [Learning to Play No-Press Diplomacy with Best Response Policy Iteration ](https://arxiv.org/abs/2006.04635) - [No Press Diplomacy: Modeling Multi-Agent Gameplay ](https://arxiv.org/abs/1909.02128) - [Agent Madoff: A Heuristic-Based Negotiation Agent For The Diplomacy Strategy Game ](https://arxiv.org/abs/1902.06996) -# Risk -- [Mini-Risk: Strategies for a Simplified Board Game](https://doi.org/10.1057/jors.1990.2) -- [A Multi-Agent System for playing the board game Risk](https://www.diva-portal.org/smash/record.jsf?pid=diva2%3A831093&dswid=-4740) -- [Learning the risk board game with classifier systems](https://doi.org/10.1145/508791.508904) -- [Markov Chains and the RISK Board Game](https://doi.org/10.1080/0025570X.1997.11996573) -- [Markov Chains for the RISK Board Game Revisited](https://doi.org/10.1080/0025570X.2003.11953165) -- [RISK Board Game ‐ Battle Outcome Analysis](http://www.c4i.gr/xgeorgio/docs/RISK-board-game%20_rev-3.pdf) -- [Planning an endgame move set for the game RISK](https://doi.org/10.1109/TEVC.2005.856211) -- [RISKy Business: An In-Depth Look at the Game RISK](https://scholar.rose-hulman.edu/rhumj/vol3/iss2/3/) -- [An Intelligent Artificial Player for the Game of Risk](http://www.ke.tu-darmstadt.de/lehre/archiv/ss04/oberseminar/folien/Wolf_Michael-Slides.pdf) +# Dominion -# Kingdomino -- [Monte Carlo Methods for the Game Kingdomino](https://doi.org/10.1109/CIG.2018.8490419) [[arXiv](https://arxiv.org/abs/1807.04458)] -- [NP-completeness of the game Kingdomino](https://arxiv.org/abs/1909.02849) +There is a [simulator](https://dominionsimulator.wordpress.com/f-a-q/) and the code behind +[the Dominion server running councilroom.com](https://github.com/mikemccllstr/dominionstats/) is available. councilroom has the [best and worst openings](http://councilroom.com/openings), [optimal card ratios](http://councilroom.com/optimal_card_ratios), [Card winning stats](http://councilroom.com/supply_win) and lots of other empirical research. -# Patchwork -- [State Representation and Polyomino Placement for the Game Patchwork](https://zayenz.se/blog/post/patchwork-modref2019-paper/) - -# Nmbr9 -- [Nmbr9 as a Constraint Programming Challenge](https://zayenz.se/blog/post/nmbr9-cp2019-abstract/) +- [Clustering Player Strategies from Variable-Length Game Logs in Dominion](https://arxiv.org/abs/1811.11273) # Hanabi - [Improving Policies via Search in Cooperative Partially Observable Games](https://arxiv.org/abs/1912.02318) (FB) [[code](https://github.com/facebookresearch/Hanabi_SPARTA)] - Current best result. @@ -118,19 +94,17 @@ If you aren't able to access any paper on this list, please [try using Sci-Hub]( - [A framework for writing bots that play Hanabi](https://github.com/Quuxplusone/Hanabi) - [Evaluating the Rainbow DQN Agent in Hanabi with Unseen Partners](https://arxiv.org/abs/2004.13291) -# Azul -- [A summary of a dissertation on Azul](https://old.reddit.com/r/boardgames/comments/hxodaf/update_i_wrote_my_dissertation_on_azul/fzd3961/?context=3) (unpublished) +# Kingdomino +- [Monte Carlo Methods for the Game Kingdomino](https://doi.org/10.1109/CIG.2018.8490419) [[arXiv](https://arxiv.org/abs/1807.04458)] +- [NP-completeness of the game Kingdomino](https://arxiv.org/abs/1909.02849) -# Monopoly -- [Negotiation strategy of agents in the MONOPOLY game](https://ieeexplore.ieee.org/abstract/document/1013210) -- [Generating interesting Monopoly boards from open data](https://ieeexplore.ieee.org/abstract/document/6374168) -- [Estimating the probability that the game of Monopoly never ends](https://ieeexplore.ieee.org/abstract/document/5429349) -- [Learning to play Monopoly:A Reinforcement Learning approach](https://www.researchgate.net/profile/Anestis_Fachantidis/publication/289403522_Learning_to_play_monopoly_A_Reinforcement_learning_approach/links/59dd1f3e458515f6efef1904/Learning-to-play-monopoly-A-Reinforcement-learning-approach.pdf) -- [Monopoly as a Markov Process](https://doi.org/10.1080/0025570X.1972.11976187) -- [Learning to Play Monopoly withMonte Carlo Tree Search](https://project-archive.inf.ed.ac.uk/ug4/20181042/ug4_proj.pdf) -- [Monopoly Using Reinforcement Learning ](https://ieeexplore.ieee.org/abstract/document/8929523) -- [A Markovian Exploration of Monopoly](https://pi4.math.illinois.edu/wp-content/uploads/2014/10/Gartland-Burson-Ferguson-Markovopoly.pdf) -- [What's the best Monopoly strategy](https://publications.lakeforest.edu/cgi/viewcontent.cgi?referer=&httpsredir=1&article=1277&context=gss) +# Lost Cities +- [Applying Neural Networks and Genetic Programming to the Game Lost Cities](http://digital.library.wisc.edu/1793/79080) + +# Mafia +- [A mathematical model of the Mafia game](https://arxiv.org/abs/1009.1031) +- [Automatic Long-Term Deception Detection in Group Interaction Videos](https://arxiv.org/abs/1905.08617) +- [Human-Side Strategies in the Werewolf Game Against the Stealth Werewolf Strategy](https://link.springer.com/chapter/10.1007/978-3-319-50935-8_9) # Magic: the Gathering - [Magic: the Gathering is as Hard as Arithmetic](https://arxiv.org/abs/2003.05119) @@ -146,36 +120,34 @@ If you aren't able to access any paper on this list, please [try using Sci-Hub]( - [Monte Carlo search applied to card selection in Magic: The Gathering](https://doi.org/10.1109/CIG.2009.5286501) - [Magic: The Gathering Deck Performance Prediction](http://cs229.stanford.edu/proj2012/HauPlotkinTran-MagicTheGatheringDeckPerformancePrediction.pdf) -# Terra Mystica -- [Using Tabu Search Algorithm for Map Generation in the Terra Mystica Tabletop Game](https://arxiv.org/abs/2006.02716) +# Modern Art: The card game +- [A constraint programming based solver for Modern Art](https://github.com/captn3m0/modernart) -# Mafia -- [A mathematical model of the Mafia game](https://arxiv.org/abs/1009.1031) -- [Automatic Long-Term Deception Detection in Group Interaction Videos](https://arxiv.org/abs/1905.08617) -- [Human-Side Strategies in the Werewolf Game Against the Stealth Werewolf Strategy](https://link.springer.com/chapter/10.1007/978-3-319-50935-8_9) +# Monopoly +- [Negotiation strategy of agents in the MONOPOLY game](https://ieeexplore.ieee.org/abstract/document/1013210) +- [Generating interesting Monopoly boards from open data](https://ieeexplore.ieee.org/abstract/document/6374168) +- [Estimating the probability that the game of Monopoly never ends](https://ieeexplore.ieee.org/abstract/document/5429349) +- [Learning to play Monopoly:A Reinforcement Learning approach](https://www.researchgate.net/profile/Anestis_Fachantidis/publication/289403522_Learning_to_play_monopoly_A_Reinforcement_learning_approach/links/59dd1f3e458515f6efef1904/Learning-to-play-monopoly-A-Reinforcement-learning-approach.pdf) +- [Monopoly as a Markov Process](https://doi.org/10.1080/0025570X.1972.11976187) +- [Learning to Play Monopoly withMonte Carlo Tree Search](https://project-archive.inf.ed.ac.uk/ug4/20181042/ug4_proj.pdf) +- [Monopoly Using Reinforcement Learning ](https://ieeexplore.ieee.org/abstract/document/8929523) +- [A Markovian Exploration of Monopoly](https://pi4.math.illinois.edu/wp-content/uploads/2014/10/Gartland-Burson-Ferguson-Markovopoly.pdf) +- [What's the best Monopoly strategy](https://publications.lakeforest.edu/cgi/viewcontent.cgi?referer=&httpsredir=1&article=1277&context=gss) -# The Resistance: Avalon -- [Finding Friend and Foe in Multi-Agent Games](https://arxiv.org/abs/1906.02330) +# Monopoly Deal +- [Implementation of AI Player on "Monopoly Deal"](https://doi.org/10.1007/978-3-662-46742-8_11) -# Ticket to Ride -- [Evolving maps and decks for ticket to ride](https://doi.org/10.1145/3235765.3235813) -- [Materials for Ticket to Ride Seattle and a framework for making more game boards](https://github.com/dovinmu/ttr_generator) -- [Applications of Graph Theory andProbability in the Board GameTicket toRide](https://www.rtealwitter.com/slides/2020-JMM.pdf) -- [The Difficulty of Learning Ticket to Ride](https://www.eecs.tufts.edu/~jsinapov/teaching/comp150_RL/reports/Nguyen_Dinjian_report.pdf) +# Nmbr9 +- [Nmbr9 as a Constraint Programming Challenge](https://zayenz.se/blog/post/nmbr9-cp2019-abstract/) -# Lost Cities -- [Applying Neural Networks and Genetic Programming to the Game Lost Cities](http://digital.library.wisc.edu/1793/79080) +# Pandemic +- [NP-Completeness of Pandemic](https://www.jstage.jst.go.jp/article/ipsjjip/20/3/20_723/_article) -# Uno -- [The complexity of UNO](https://arxiv.org/abs/1003.2851) -- [UNO Is Hard, Even for a Single Player](https://doi.org/10.1007/978-3-642-13122-6_15) +# Patchwork +- [State Representation and Polyomino Placement for the Game Patchwork](https://zayenz.se/blog/post/patchwork-modref2019-paper/) -# Dominion - -There is a [simulator](https://dominionsimulator.wordpress.com/f-a-q/) and the code behind -[the Dominion server running councilroom.com](https://github.com/mikemccllstr/dominionstats/) is available. councilroom has the [best and worst openings](http://councilroom.com/openings), [optimal card ratios](http://councilroom.com/optimal_card_ratios), [Card winning stats](http://councilroom.com/supply_win) and lots of other empirical research. - -- [Clustering Player Strategies from Variable-Length Game Logs in Dominion](https://arxiv.org/abs/1811.11273) +# Pentago +- [On Solving Pentago](http://www.ke.tu-darmstadt.de/lehre/arbeiten/bachelor/2011/Buescher_Niklas.pdf) # Quixo - [QUIXO is EXPTIME-complete](https://doi.org/10.1016/j.ipl.2020.105995) @@ -183,30 +155,57 @@ There is a [simulator](https://dominionsimulator.wordpress.com/f-a-q/) and the c # Race for the Galaxy - [SCOUT: A Case-Based Reasoning Agent for Playing Race for the Galaxy](https://doi.org/10.1007/978-3-319-61030-6_27) +# The Resistance: Avalon +- [Finding Friend and Foe in Multi-Agent Games](https://arxiv.org/abs/1906.02330) + +# Risk +- [Mini-Risk: Strategies for a Simplified Board Game](https://doi.org/10.1057/jors.1990.2) +- [A Multi-Agent System for playing the board game Risk](https://www.diva-portal.org/smash/record.jsf?pid=diva2%3A831093&dswid=-4740) +- [Learning the risk board game with classifier systems](https://doi.org/10.1145/508791.508904) +- [Markov Chains and the RISK Board Game](https://doi.org/10.1080/0025570X.1997.11996573) +- [Markov Chains for the RISK Board Game Revisited](https://doi.org/10.1080/0025570X.2003.11953165) +- [RISK Board Game ‐ Battle Outcome Analysis](http://www.c4i.gr/xgeorgio/docs/RISK-board-game%20_rev-3.pdf) +- [Planning an endgame move set for the game RISK](https://doi.org/10.1109/TEVC.2005.856211) +- [RISKy Business: An In-Depth Look at the Game RISK](https://scholar.rose-hulman.edu/rhumj/vol3/iss2/3/) +- [An Intelligent Artificial Player for the Game of Risk](http://www.ke.tu-darmstadt.de/lehre/archiv/ss04/oberseminar/folien/Wolf_Michael-Slides.pdf) + # Santorini - [A Mathematical Analysis of the Game of Santorini](https://openworks.wooster.edu/independentstudy/8917/) -# Set +# Scotland Yard +- [The complexity of Scotland Yard](http://www.illc.uva.nl/Research/Publications/Reports/PP-2006-18.text.pdf) +# Set Set has a long history of mathematical research, so this list isn't exhaustive. - [Game, Set, Math](https://doi.org/10.4169/math.mag.85.2.083) - [The Joy of SET](https://doi.org/10.1080/00029890.2018.1412661) -# Pentago -- [On Solving Pentago](http://www.ke.tu-darmstadt.de/lehre/arbeiten/bachelor/2011/Buescher_Niklas.pdf) +# Settlers of Catan +- [The effectiveness of persuasion in The Settlers of Catan ](https://doi.org/10.1109/CIG.2014.6932861) +- [Avoiding Revenge Using Optimal Opponent Ranking Strategy in the Board Game Catan ](https://doi.org/10.4018/IJGCMS.2018040103) +- [Game strategies for The Settlers of Catan](https://doi.org/10.1109/CIG.2014.6932884) +- [Monte-Carlo Tree Search in Settlers of Catan](https://doi.org/10.1007/978-3-642-12993-3_3) +- [Settlers of Catan bot trained using reinforcement learning (MATLAB).](https://jonzia.github.io/Catan/) +- [Trading in a multiplayer board game: Towards an analysis of non-cooperative dialogue](https://escholarship.org/content/qt9zt506xx/qt9zt506xx.pdf) +- [POMCP with Human Preferencesin Settlers of Catan](https://www.aaai.org/ocs/index.php/AIIDE/AIIDE18/paper/viewFile/18091/17217) +- [Reinforcement Learning of Strategies for Settlers of Catan](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.561.6293&rep=rep1&type=pdf) +- [Deep Reinforcement Learning in Strategic Board GameEnvironments](https://doi.org/10.1007/978-3-030-14174-5_16) [[pdf](https://hal.archives-ouvertes.fr/hal-02124411/document)] +- [Monte Carlo Tree Search in a Modern Board Game Framework](https://project.dke.maastrichtuniversity.nl/games/files/bsc/Roelofs_Bsc-paper.pdf) +- [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) -# Blokus -- [Blokus Game Solver](https://digitalcommons.calpoly.edu/cpesp/290/) +# Terra Mystica +- [Using Tabu Search Algorithm for Map Generation in the Terra Mystica Tabletop Game](https://arxiv.org/abs/2006.02716) -# Pandemic -- [NP-Completeness of Pandemic](https://www.jstage.jst.go.jp/article/ipsjjip/20/3/20_723/_article) +# Ticket to Ride +- [Evolving maps and decks for ticket to ride](https://doi.org/10.1145/3235765.3235813) +- [Materials for Ticket to Ride Seattle and a framework for making more game boards](https://github.com/dovinmu/ttr_generator) +- [Applications of Graph Theory andProbability in the Board GameTicket toRide](https://www.rtealwitter.com/slides/2020-JMM.pdf) +- [The Difficulty of Learning Ticket to Ride](https://www.eecs.tufts.edu/~jsinapov/teaching/comp150_RL/reports/Nguyen_Dinjian_report.pdf) -# Scotland Yard -- [The complexity of Scotland Yard](http://www.illc.uva.nl/Research/Publications/Reports/PP-2006-18.text.pdf) - -# Monopoly Deal -- [Implementation of AI Player on "Monopoly Deal"](https://doi.org/10.1007/978-3-662-46742-8_11) +# Uno +- [The complexity of UNO](https://arxiv.org/abs/1003.2851) +- [UNO Is Hard, Even for a Single Player](https://doi.org/10.1007/978-3-642-13122-6_15) # Yahtzee - [Optimal Solitaire Yahtzee Strategies](http://www.yahtzee.org.uk/optimal_yahtzee_TV.pdf)