An open framework for the reproducible study of the iterated prisoner's dilemma

The Axelrod library is an open source Python package that allows for reproducible game theoretic research into the Iterated Prisoner’s Dilemma. This area of research began in the 1980s but suffers from a lack of documentation and test code. The goal of the library is to provide such a resource, with facilities for the design of new strategies and interactions between them, as well as conducting tournaments and ecological simulations for populations of strategies. With a growing collection of 139 strategies, the library is a also a platform for an original tournament that, in itself, is of interest to the game theoretic community. This paper describes the Iterated Prisoner’s Dilemma, the Axelrod library and its development, and insights gained from some novel research.

[1]  Kenji Takeda,et al.  Top Tips to Make Your Research Irreproducible , 2015, ArXiv.

[2]  Yosuke Fukuda,et al.  Rational Cooperation in the Finitely Repeated Prisoners' Dilemma , 2013 .

[3]  D. Kraines,et al.  Pavlov and the prisoner's dilemma , 1989 .

[4]  J. Banks,et al.  Repeated games, finite automata, and complexity , 1990 .

[5]  Wolfgang Kienreich,et al.  On some winning strategies for the Iterated Prisoner's Dilemma or Mr. Nice Guy and the Cosa Nostra , 2006, ArXiv.

[6]  D. Stephens,et al.  Discounting and Reciprocity in an Iterated Prisoner's Dilemma , 2002, Science.

[7]  R. Axelrod.  Effective Choice in the Prisoner's Dilemma , 1980 .

[8]  Anton Nekrutenko,et al.  Ten Simple Rules for Reproducible Computational Research , 2013, PLoS Comput. Biol..

[9]  Roderick M. Kramer,et al.  When in Doubt... , 1991 .

[10]  Prasanth H. Nair,et al.  Astropy: A community Python package for astronomy , 2013, 1307.6212.

[11]  P. Molander.  The Optimal Level of Generosity in a Selfish, Uncertain Environment , 1985 .

[12]  Erhan Bilal,et al.  Improving Breast Cancer Survival Analysis through Competition-Based Multidimensional Modeling , 2013, PLoS Comput. Biol..

[13]  Gaël Varoquaux,et al.  Scikit-learn: Machine Learning in Python , 2011, J. Mach. Learn. Res..

[14]  Glenn Ellison.  Cooperation in the Prisoner's Dilemma with Anonymous Random Matching , 1994 .

[15]  David B. Fogel,et al.  Evolution, neural networks, games, and intelligence , 1999, Proc. IEEE.

[16]  M M Kuftinec,et al.  When in doubt... , 1995, American journal of orthodontics and dentofacial orthopedics : official publication of the American Association of Orthodontists, its constituent societies, and the American Board of Orthodontics.

[17]  Nicholas Mark Gotts,et al.  Agent-Based Simulation in the Study of Social Dilemmas , 2003, Artificial Intelligence Review.

[18]  Michael M. McKerns,et al.  Building a Framework for Predictive Science , 2012, SciPy.

[19]  Graham Kendall,et al.  Engineering Design of Strategies for Winning Iterated Prisoner's Dilemma Competitions , 2011, IEEE Transactions on Computational Intelligence and AI in Games.

[20]  J. Lorberbaum,et al.  No strategy is evolutionarily stable in the repeated prisoner's dilemma. , 1994, Journal of theoretical biology.

[21]  W. Press,et al.  Iterated Prisoner’s Dilemma contains strategies that dominate any evolutionary opponent , 2012, Proceedings of the National Academy of Sciences.

[22]  M. Nowak,et al.  Adaptive Dynamics of Extortion and Compliance , 2013, PloS one.

[23]  Wes McKinney,et al.  Data Structures for Statistical Computing in Python , 2010, SciPy.

[24]  Andreas Prlic,et al.  Ten Simple Rules for the Open Development of Scientific Software , 2012, PLoS Comput. Biol..

[25]  C. Hauert,et al.  Models of cooperation based on the Prisoner's Dilemma and the Snowdrift game , 2005 .

[26]  Alvin E. Roth,et al.  Expecting Continued Play in Prisoner's Dilemma Games , 1983 .

[27]  Andrew McLennan,et al.  Gambit: Software Tools for Game Theory , 2006 .

[28]  R. Boyd,et al.  No pure strategy is evolutionarily stable in the repeated Prisoner's Dilemma game , 1987, Nature.

[29]  Alan G. Isaac.  Simulating Evolutionary Games: A Python-Based Introduction , 2008, J. Artif. Soc. Soc. Simul..

[30]  W. Hamilton,et al.  The evolution of cooperation. , 1984, Science.

[31]  R. Axelrod.  More Effective Choice in the Prisoner's Dilemma , 1980 .

[32]  Xin Yao,et al.  The Iterated Prisoners' Dilemma - 20 Years On , 2007, Advances in Natural Computation.

[33]  John D. Hunter,et al.  Matplotlib: A 2D Graphics Environment , 2007, Computing in Science & Engineering.

[34]  Alexander J. Stewart,et al.  Extortion and cooperation in the Prisoner’s Dilemma , 2012, Proceedings of the National Academy of Sciences.

[35]  M. Dufwenberg.  Game theory. , 2011, Wiley interdisciplinary reviews. Cognitive science.

[36]  Marc Harper,et al.  The Art of War: Beyond Memory-one Strategies in Population Games , 2014, PLoS ONE.

[37]  David B. Fogel,et al.  Evolving Behaviors in the Iterated Prisoner's Dilemma , 1993, Evolutionary Computation.

[38]  Jia-Wei Li.  How to Design a Strategy to Win an IPD Tournament , 2006 .

[39]  Kenji Takeda,et al.  """"Share and Enjoy"""": Publishing Useful and Usable Scientific Models , 2014, 2014 IEEE/ACM 7th International Conference on Utility and Cloud Computing.