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Merge pull request #28 from gambitproject/add-hidden-history
Add "about" page
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config.yaml

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description:
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- "Gambit is a set of software tools for doing computation on finite, noncooperative games in extensive or strategy form and a set of file formats for storing and communicating games to external tools."
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- "The Gambit Project was founded in the mid-1980s at the California Institute of Technology and to this day is actively developed by a community of contributors, with core development led by [The Alan Turing Institute](https://www.turing.ac.uk) as part of its project: [Automated analysis of strategic interactions](https://www.turing.ac.uk/research/research-projects/automated-analysis-strategic-interactions)."
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# timeline:
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# image: gambit_timeline.svg
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# title: "Through the years"
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# subtitle: "The tools for computational game theory research, from BASIC to the language model era."
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software_title: "Open source & free to use"
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software:
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- name: PyGambit

content/about.md

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---
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title: About Gambit
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---
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Gambit is a set of software tools for doing computation on finite,
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noncooperative games. These comprise a graphical interface for
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interactively building and analyzing general games in extensive or
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strategy form; a number of command-line tools for computing Nash
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equilibria and other solution concepts in games; and, a set of file
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formats for storing and communicating games to external tools.
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Gambit is fully-cross platform, and is supported on Linux, Mac OS X,
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and Microsoft Windows.
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Key features of Gambit
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======================
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Gambit has a number of features useful both for the researcher and the
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instructor:
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**Interactive, cross-platform graphical interface.** All Gambit
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features are available through the use of a graphical interface, which
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runs under multiple operating systems: Windows, various flavors of
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Un*x (including Linux), and Mac OS X. The interface offers flexible
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methods for creating extensive and strategic games. It offers an
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interface for running algorithms to compute Nash equilibria, and for
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visualizing the resulting profiles on the game tree or table, as well
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as an interactive tool for analyzing the dominance structure of
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actions or strategies in the game. The interface is useful for the
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advanced researcher, but is intended to be accessible for students
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taking a first course in game theory as well.
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**Command-line tools for computing equilibria.** More advanced
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applications often require extensive computing time and/or the ability
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to script computations. All algorithms in Gambit are packaged as
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individual, command-line programs, whose operation and output are
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configurable.
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**Extensibility and interoperability.** The Gambit tools read and
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write file formats which are textual and documented, making them
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portable across systems and able to interact with external tools. It
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is therefore straightforward to extend the capabilities of Gambit by,
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for example, implementing a new method for computing equilibria,
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reimplementing an existing one more efficiently, or creating tools to
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programmatically create, manipulate, and transform games, or for
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econometric analysis on games.
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Limitations of Gambit
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=====================
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Gambit has a few limitations that may be important in some
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applications. We outline them here.
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**Gambit is for finite games only.** Because of the mathematical
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structure of finite games, it is possible to write many general-
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purpose routines for analyzing these games. Thus, Gambit can be used
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in a wide variety of applications of game theory. However, games that
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are not finite, that is, games in which players may choose from a
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continuum of actions, or in which players may have a continuum of
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types, do not admit the same general-purpose methods.
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**Gambit is for noncooperative game theory only.** Gambit focuses on
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the branch of game theory in which the rules of the game are written
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down explicitly, and in which players choose their actions
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independently. Gambit's analytical tools center primarily around Nash
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equilibrium, and related concepts of bounded rationality such as
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quantal response equilibrium. Gambit does not at this time provide any
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representations of, or methods for, analyzing games written in
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cooperative form. (It should be noted that some problems in
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cooperative game theory do not suffer from the computational
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complexity that the Nash equilibrium problem does, and thus
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cooperative concepts could be an interesting future direction of
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development.)
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**Analyzing large games may become infeasible surprisingly quickly.**
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While the specific formal complexity classes of computing Nash
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equilibria and related concepts are still an area of active research,
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it is clear that, in the typical case, the amount of time required to
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compute equilibria increases rapidly in the size of the game. In other
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words, it is quite easy to write down games which will take Gambit an
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unacceptably long amount time to compute the equilibria of. There are
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two ways to deal with this problem in practice. One way is to better
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identify good heuristic approaches for guiding the equilibrium
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computation process. Another way is to take advantage of known
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features of the game to guide the process. Both of these approaches
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are now becoming areas of active interest. While it will certainly not
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be possible to analyze every game that one would like to, it is hoped
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that Gambit will both contribute to these two areas of research, as
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well as make the resulting methods available to both students and
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practitioners.
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Who built Gambit?
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=================
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Check out the [team page](/team/) on the Gambit website for up-to-date information on the current Gambit development team.
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History
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-------
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The principal developers of Gambit have been:
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* [Theodore Turocy](http://www.gambit-project.org/turocy),
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University of East Anglia: director.
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* Richard D. McKelvey, California Institute of Technology:
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project founder.
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* Andrew McLennan, University of Queensland: co-PI during main
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development, developer and maintainer of polynomial-based algorithms
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for equilibrium computation.
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Much of the development of the main Gambit codebase took place in
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1994-1996, under a grant from the National Science Foundation to the
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California Institute of Technology and the University of Minnesota
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(McKelvey and McLennan, principal investigators).
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Others contributing to the development and distribution of Gambit
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include:
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* Bernhard von Stengel provided advice on implementation of
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sequence form code, and contributed clique code
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* Eugene Grayver developed the first version of the
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graphical user interface.
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* Gary Wu implemented an early scripting language interface for
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Gambit (since superseded by the Python API).
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* Stephen Kunath and Alessandro Andrioni did extensive work to create
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the first release of the Python API.
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* From Gambit 14, Gambit contains support for Action Graph Games
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[Jiang11]_. This has been contributed by Navin Bhat, Albert Jiang,
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Kevin Leyton-Brown, and David Thompson, with funding support
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provided by a University Graduate Fellowship of the University
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of British Columbia, the NSERC Canada Graduate Scholarship, and a
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Google Research Award to Leyton-Brown.
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The Gambit Project was founded in the mid-1980s by Richard McKelvey at
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the California Institute of Technology. The original implementation
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was written in BASIC, with a simple graphical interface. This code was
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ported to C around 1990 with the help of Bruce Bell, and was
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distributed publicly as version 0.13 in 1991 and 1992.
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A major step in the evolution of Gambit took place with the awarding
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of the NSF grants in 1994, with McKelvey and Andrew McLennan as
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principal investigators, and [Theodore Turocy](http://www.gambit-project.org/turocy) as the head programmer.
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The grants sponsored a complete rewrite of Gambit in C++. The
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graphical interface was made portable across platforms through the use
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of the [wxWidgets library](http://www.wxwidgets.org). Version 0.94 of Gambit was released in
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the late summer of 1994, version 0.96 followed in 1999, and version
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0.97 in 2002. During this time, many students at Caltech and Minnesota
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contributed to the effort by programming, testing, and/or documenting.
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These include, alphabetically, Bruce Bell, Anand Chelian, Matthew
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Derer, Nelson Escobar, Ben Freeman, Eugene Grayver, Todd Kaplan, Geoff
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Matters, Brian Trotter, Michael Vanier, Roberto Weber, and Gary Wu.
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Over the same period, Bernhard von Stengel, of the London School of
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Economics, made significant contributions in the implementation of the
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sequence form methods for two-player extensive games, and for
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contributing his "clique" code for identification of equilibrium
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components in two-player strategic games, as well as other advice
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regarding Gambit's implementation and architecture.
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Development since the mid-2000s has focused on two objectives. First,
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the graphical interface was reimplemented and modernized, with the
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goal of following good interaction design principles, especially in
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regards to easing the learning curve for users new to Gambit and new
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to game theory. Second, the internal architecture of Gambit was
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refactored to increase interoperability between the tools provided by
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Gambit and those written independently.
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Gambit is proud to have participated in the Google Summer of Code
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program in the summers of 2011 and 2012 as a mentoring organization.
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The Python API, which became part of Gambit from Gambit 13, was
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developed during these summers, thanks in particular to the work
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of Stephen Kunath and Alessandro Andrioni.

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