Install#

Users installing Gambit have several options depending on their needs and their operating system. We recommended most new users install the PyGambit package and read the PyGambit documentation.

Developers & contributors should refer to the developer docs which contain guides for building Gambit from source and contributing to the project.

Installing PyGambit#

PyGambit is available on PyPI. We recommend installing it into a Python virtual environment via pip:

pip install pygambit

To install a specific older version:

pip install pygambit==X.Y.Z

Releases#

The current stable release of Gambit is 16.6.0.

Install on Windows

  1. Download the installer:

    Download the .msi for Gambit 16.6.0 from the GitHub releases page.

  2. Run the installer:

    Double-click the downloaded .msi file and follow the on-screen instructions to complete the installation.

Install on macOS with disk image

  1. Download the .dmg installer:

    Download the .dmg for Gambit 16.6.0 from the GitHub releases page.

  2. Install the application:

    Double-click the .dmg file to mount it, then drag the Gambit application to your Applications folder.

Warning

Gambit’s macOS application is not signed or notarized by Apple. Gatekeeper will block opening it by default.

To open it anyway, right-click (or Control-click) the Gambit application and choose Open from the context menu, then confirm in the dialog that appears. Alternatively, go to System Settings → Privacy & Security and click Open Anyway after the first blocked launch attempt.

If your administrator privileges prevent this, use the Homebrew installation or build from source (see the developer build instructions).

Install on macOS via Homebrew

  1. Check that you have Homebrew installed by running brew –version. If not, follow the instructions at https://brew.sh/.

  2. Install Gambit using Homebrew:

    brew install gambit

Warning

Homebrew installation has not been set up or tested by the Gambit development team.

Install on Linux or macOS from source tarball

  1. Download the source tarball:

    Download the source tarball for Gambit 16.6.0 from the GitHub releases page.

  2. Extract the tarball:

    Once downloaded, extract the tarball using the following command:

    tar -xzf gambit-|release|.tar.gz

  3. Build and install Gambit:

    Navigate to the extracted directory and run:

    ./configure
make
sudo make install

    Note

    Command-line options are available to modify the configuration process; do ./configure –help for information. Of these, the option which may be most useful is to disable the build of the graphical interface.

    By default Gambit will be installed in /usr/local. You can change this by replacing configure step with one of the form

    `./configure --prefix=/your/path/here`

    Warning

    The graphical interface relies on external calls to other programs built in this process, especially for the computation of equilibria. It is strongly recommended that you install the Gambit executables to a directory in your path!

All past releases are available on the GitHub releases page.

Changelog#

[16.7.0] - unreleased#

Added#

  • Added Player.sequences as the collection of sequences available to a player.

  • Implement GameSubgameRep (C++) and Subgame (Python), a first-class object representing a subgame. (#585)

  • Games can be materialised directly from OpenSpiel games if pyspiel is installed. (#917)

  • Magnify events are now supported in GUI for zooming in/out on trees.

Fixed#

  • Corrected resizing of row and column index labels in strategic form so pivoting works correctly. (#844)

  • Corrected incorrect output of strategic game tables to .nfg files if strategies have previously been deleted in the game (#875)

  • Fix incorrect row index checking in swapping rows of a rectangular array (leading to errors in for example simpdiv_solve) (#868)

  • In GUI, typing a payoff with a trailing slash is now interpreted as a whole number (previously this led to a validation error dialog)

  • Improved initial zoom and centering of display of game trees on initial load, and focusing behavior on currently-selected node or jumping to the root. Also adjusted the initial size of the game window to a more comfortable size. (#569)

  • In the GUI, tab-traversal on tables (such as the strategic form payoff table) now works as expected (TAB moves one cell to the right, wrapping if appropriate; SHIFT-TAB moves to the left, wrapping if appropriate).

  • Max regret is calculated correctly for strategy and behavior profiles on games with zero player strategies or actions (is defined to be 0 trivially) (#904)

  • Corrected calculation of total number of actions for a player in pygambit (#938)

  • Corrected a regression in action graph games that left the internal data structure not fully initialised, leading to segmentation faults.

Changed#

  • Added a new welcome/landing window on launching the GUI without a game. This has the effect of avoiding creating a window with a trivial extensive game which the user then has to dismiss if they do not require it. (#80)

  • Clarified handling of .efg/.nfg/.gbt file types in graphical interface and refined warnings about unsaved work. (#12)

  • Created and documented right-click context menu in the normal form pivot table, which makes the mechanism for deleting a strategy more clear. (#855)

  • Payoff editing in extensive games in the graphical interface is now done via a context popup window rather than text controls drawn (not always well!) over the game tree display. (#947)

  • In pygambit, indexing game object collections by integer position has been removed. (#942)

Removed#

  • Built-in plotting of logit QRE for strategic games has been removed in the GUI (#809)

[16.6.0] - 2026-03-24#

Changed#

  • Gambit has a refreshed branding and logo which is reflected in this release!

  • Game.comment has been renamed to Game.description

  • With behaviour profiles that reach some information sets with probability zero, beliefs, action values, and infoset values are not well-defined. These functions now return a std::optional in C++ and type or None in Python, where nulls indicate these quantities are not defined. (#446)

Added#

  • Implement linear-time algorithm to find all root nodes of proper subgames, using an adaptation of Tarjan’s (1974) algorithm for finding bridges in an undirected graph. Subgame roots are cached so subsequent lookup is constant-time (if the game is unchanged). (#584)

Fixed#

  • enumpoly would take a very long time on some supports where an equilibrium is located on the boundary of the projected game. Search is now restricted to the interior of the space ruling these out; these will always be found by another projection. (#756)

  • In the graphical interface, the logit correspondence display would fail and terminate the program on very small (<10^{-300}) probabilities.

  • The new subgame root computation fixes a bug which failed to detect subgames where the subgame root node is a member of an absent-minded infoset. (#584)

  • Removed spurious warning in graphical interface when loading file as a command-line argument (or also by clicking on a file in MSW, as that uses the command-line mechanism). (#801)

  • Game.reveal raised a null pointer access exception or dumped core in some cases (#749)

[16.5.0] - 2026-01-05#

Fixed#

  • Sequence-form based equilibrium-finding methods returned incorrect output on games with outcomes at non-terminal nodes. (#654)

Added#

  • Implement IsAbsentMinded() on information sets (C++) and Infoset.is_absent_minded (Python) to detect if an information is absent-minded.

  • Tests for EFG Nash solvers – enumpoly_solve, lp_solve, lcp_solve – in behavior strategies

  • In pygambit, Node objects now have a read-only property own_prior_action and Infoset objects have a read-only property own_prior_actions to retrieve the last action or the set of last actions taken by the player before reaching the node or information set, respectively. (#582)

  • In pygambit, Node objects now have a read-only property is_strategy_reachable to determine if the node is reachable by at least one pure strategy profile. This proves useful for identifying unreachable parts of the game tree in games with absent-mindedness. (#629)

Changed#

  • Labels for players, outcomes, strategies, and actions are expected to be non-empty and unique within the relevant scope (games for players and outcomes, players for strategies, and information sets for actions). pygambit now issues a FutureWarning if a label is changed that does not conform to these expectations. There is now an optional flag normalize_labels to read_* which will automatically fill in non-confirming sets of labels. In version 16.6 these will be enforced; invalid label sets will generate an error and files will be normalized automatically on read. (#614)

  • Terminology for agent-form calculations on extensive games has been clarified. Mixed behavior profiles distinguish “agent” regret and liap values from their strategy-based analogs. Methods which compute using the agent-form - specifically enumpure_solve and liap_solve, now clarify this by being named differently in pygambit. (#617)

  • For clarity, the stop_after and max_depth arguments to lcp_solve are no longer permitted when solving using the sequence form. These actually had no effect in previous versions. (#671)

  • In the graphical interface, removed option to configure information set link drawing; information sets are always drawn and indicators are always drawn if an information set spans multiple levels.

  • In pygambit, indexing the children of a node by a string inteprets the string as an action label, not a label of a child node. In addition, indexing by an action object is now supported. (#587)

  • In pygambit, min_payoff and max_payoff (for both games and players) now refers to payoffs in any play of the game; previously this referred only to the set of outcomes. (#498)

  • In pygambit, calls to sort_infosets are no longer required to normalise the game representation. Iteration ordering of information sets and their members is ensured internally. sort_infosets is therefore now a no-op and is deprecated; it will be removed in a future version.

Removed#

  • Eliminating dominated actions has been removed from the GUI as it was implementing a non-standard formulation of dominance. (#612)

  • The C++ method for computing subgame perfect equilibria with selected methods has been removed (and as a result from the enumpure, lp, and lcp command-line tools); this will be replaced with new and more customisable approaches. (#639)

[16.4.1] - 2025-12-17#

Fixed#

  • Fixed a regression in which null outcomes in strategic game tables were not handled correctly when changing the number of strategies in the game (#571)

  • Fixed improper shared pointer handling when writing a .nfg file based on a game in extensive form.

  • Fixed a regression in the GUI in which unique action labels were not being generated when adding a move via drag-and-drop of a player icon (#618)

  • Fixed a regression generating null pointer dereference errors when setting the outcome of a node to the null outcome (#625, #647)

  • Fixed a regression in calculating payoff quantities for mixed strategy profiles derived from mixed behavior profiles (#616)

[16.3.2] - 2025-12-04#

Fixed#

  • Parsing of output of gambit-logit in the graphical interface did not handle the terminal Nash profile correctly. (#172)

  • Improved sizing of list of logit profiles computed for normal form games.

Changed#

  • Removed Ctrl/Cmd-X accelerator for closing program, as this clashes with modern standard expectations. (#507)

Removed#

  • Undo and redo have been removed from the graphical interface. (These were meant to be removed previously as they did not work properly and gave unpredictable behaviour.) (#505)

[16.4.0] - 2025-09-05#

General#

  • Officially added support for Python 3.13.

  • For graphical interface, added support for wxWidgets 3.3; require minimum of wxWidgets 3.2.

Removed#

  • The deprecated functions Game.read_game, Game.parse_game and Game.write functions have been removed as planned. (#357)

Added#

  • Implement GetPlays() (C++) and get_plays (Python) to compute the set of terminal nodes consistent with a node, information set, or action (#517)

  • Implement GameStrategyRep::GetAction (C++) and Strategy.action (Python) retrieving the action prescribed by a strategy at an information set

  • Tests for creation of the reduced strategic form from an extensive-form game (currently only for games with perfect recall)

  • Implement Nodes collection as a member of GameRep, including a C++ iterator that returns nodes in depth-first traversal order (#530)

Changed#

  • Internally in C++ std::shared_ptr are now used to manage memory allocated for game objects. (#518)

  • The iteration order of a player’s information sets, and of the members of an information set, now may depend on the order of operations to build a game tree. The previous behaviour - ensuring sorting by the order encountered in a depth-first traversal of the tree - can now be obtained by calling SortInfosets (C++) or sort_infosets (Python) on the game. (#483)

[16.3.1] - 2025-08-18#

Fixed#

  • Corrected a regression in which information sets were prematurely invalidated (and therefore delete this called on them) when removing the last node from an information set.

[16.3.0] - 2025-01-13#

General#

  • Dropped support for Python 3.8.

Added#

  • Implemented maximum-likelihood estimation for agent logit QRE, to parallel existing support for strategic logit QRE. Strategic logit QRE function names have been modified to provide parallel naming. Estimation using the correspondence now supports an option to stop at the first interior local maximizer found (if one exists).

  • Maximum-likelihood estimation for logit QRE using empirical payoffs has an improved internal calculation of log-likelihood, and returns the estimated profile instead of just a list of probabilities.

  • Reorganized naming conventions in pygambit for functions for computing QRE in both strategic and agent versions, and added a corresponding section in the user guide.

  • enumpoly_solve has been returned to being fully supported from temporarily being experimental; now available in pygambit.

  • enumpoly_solve for strategic games now uses the Porter, Nudelman, and Shoham (2004) ordering of supports to search.

  • to_arrays converts a Game to a list of numpy arrays containing its reduced strategic form. (#461)

  • Integrated support (in Python) for using PHCpack to solve systems of polynomial equations in enumpoly_solve based on an implementation formerly in the contrib section of the repository. (#165)

  • New format-specific functions pygambit.read_* and pygambit.Game.to_* functions have been added to (de-)serialise games. The existing Game.read_game and Game.write functions have been deprecated and will be removed in 16.4. (#357)

Changed#

  • The built-in implementation of lrslib (dating from 2016) has been removed. Instead, access to lrsnash is provided as an external tool via the enummixed_solve function, in parallel to PHCpack for enumpoly_solve.

Fixed#

  • When parsing .nfg files, check that the number of outcomes or payoffs is the expected number, and raise an exception if not. (#119)

Removed#

  • Game.write() no longer supports generation of the XML-format files for Game Theory Explorer, as GTE no longer reads files in this format.

[16.2.2] - 2025-08-18#

Fixed#

  • Game.copy_tree and Game.move_tree implementations reversed the roles of the src and dest nodes (#499)

Changed#

  • For graphical interface, added support for wxWidgets 3.3; require minimum of wxWidgets 3.2.

[16.2.1] - 2025-01-06#

Fixed#

  • Corrected an internal implementation error in Game.reveal() in resolving references to information sets and players (#453)

  • Reading .efg and .nfg game files which did not have whitespace at the end would lead to an infinite loop (#457)

  • Attempting to call the default constructor on Game objects (rather than one of the factory functions) now raises a more informative exception (#463)

[16.2.0] - 2024-04-05#

Fixed#

  • gnm_solve/gambit-gnm now correctly handles the degenerate case of a game where all payoffs are the same (#405), and checks that the perturbation vector specified has at least one non-zero component (#194)

  • ipa_solve/gambit-ipa ensures the use of a generic perturbation vector; this resolves a problem where the method could return non-Nash output (#406)

  • gambit-enumpoly could get stuck in an infinite loop, and/or fail to report some equilibria, due to floating-point rounding/tolerance issues; this has been fixed on known cases (#198)

  • gambit-logit now uses perturbations to attempt to resolve correspondences that have bifurcations, and instead tries always to follow a curve that has the same orientation. This should eliminate cases in which tracing gets stuck in a loop or reverses itself when encountering bifurcations (#3)

Added#

  • MixedStrategyProfile and MixedBehaviorProfile objects in pygambit can now be iterated in various dict-like ways

  • gnm_solve/gambit-gnm now exposes several parameters which control the behavior of the path-following procedure

  • The MixedBehaviorProfile object can now be initialized on creation by a given distribution.

  • append_move/append_infoset now resolves either a singleton node reference or any iterable set of node references

  • Additional regret-related functions added to MixedBehaviorProfile and MixedStrategyProfile in both C++ and Python

  • Some caching added to payoff/strategy value calculations in MixedStrategyProfile

  • gambit-simpdiv now supports expressing output as floating-point with a specified number of digits (#296)

  • Parameters first_step and max_accel added to gambit_logit for finer control of numerical continuation process

Changed#

  • Gambit now requires a compiler that supports C++17.

  • Functions to compute Nash equilibria now return a NashComputationResult object instead of a bare list of profiles (#190)

  • liap_solve/gambit-liap has been reimplemented to scale payoffs uniformly across games, to always take an explicit starting point (in liap_solve), and to specify a regret-based acceptance criterion (#330)

  • simpdiv_solve/gambit-simpdiv now accepts a regret-based acceptance criterion (#439)

  • simpdiv_solve now takes an explicit starting point (#445)

  • Converted test suite for mixed behavior profiles to pytest style; added parametrizations for test_realiz_prob; added test_martingale_property_of_node_value (#375)

  • Improved test suite for mixed strategy profiles (#374)

  • Test suite for pygambit moved from src/pygambit/tests/ to tests/

  • Improved repr methods in pygambit for game-related classes

  • Further extension of test suite for mixed behavior profiles to cover new indexing and profile order consistency for payoff-related calculations

  • Overhaul of caching in MixedBehaviorProfile to use maps (std::map)

  • Creation of random mixed profiles in pygambit is done with new Game.random_strategy_profile and Game.random_behavior_profile methods; these accept numpy.random.Generator objects for reproducible state. Creation of random mixed profiles in C++ is done with new Game::NewRandomStrategyProfile and Game::NewRandomBehaviorProfile methods; these accept STL Generator objects for reproducible state. The Python implementation is no longer just a wrapper around the C++ one.

  • Graphical interface now uses simplicial subdivision as the recommended method for finding some equilibria in games with more than two players, instead of Lyapunov function minimisation

[16.1.1] - 2024-01-10#

Fixed#

  • In gambit-logit, if there are chance actions with zero probability, information sets may be reached with zero probability. In this event, gambit-logit treats beliefs at those information sets as being uniform across nodes (#63)

  • Corrected outdated code in fit_fixedpoint and fit_empirical, and added extended documentation of both methods (#1)

  • Fixed bug in gambit-lp which would return non-Nash output on extensive games if the game had chance nodes other than the root node (#134)

  • In pygambit, fixed indexing in mixed behavior and mixed strategy profiles, which could result in strategies or actions belonging to other players or information sets being referenced when indexing by string label

Changed#

  • In pygambit, resolving game objects with ambiguous or duplicated labels results in a ValueError, instead of silently returning the first matching object found.

[16.1.0] - 2023-11-09#

Fixed#

  • Fixed regression in Game.from_dict() causing the method to fail (PR #399 by AbhijeetKrishnan)

  • In gambit-logit on extensive games, a spurious final value was being emitted on each line of the CSV output; this has been removed.

[16.1.0b1] - 2023-11-06#

Added#

  • Implement MixedBehaviorProfile.realiz_prob to return probability node is reached under the profile.

Fixed#

  • When an action at a chance node is deleted the probabilities for the remaining actions are normalized.

Changed#

  • The gambit-enumpoly solver has been marked as “experimental” and is no longer built by default, nor is it available via the graphical interface.

[16.1.0a4] - 2023-10-13#

Changed#

  • Empty or all-whitespace strings cannot be used to access members of games in pygambit.

  • Remaining compatibility code for wxWidgets 2.x removed from graphical interface.

  • Migrated to pytest for testing of pygambit.

  • ValueErrors raised for mixed behavior profiles when payoff, action_value, or infoset_value are called with the chance player.

  • Implemented Game.delete_strategy to remove a strategy from a strategic game.

  • Implemented regret for mixed strategy profiles.

Fixed#

  • Regret on mixed behavior profiles now implements the standard definition of regret (loss in expected payoff relative to best response conditional on reaching the information set).

[16.1.0a3] - 2023-09-29#

Changed#

  • The refine and leash parameters to simpdiv have been made available and documented in pygambit.

  • Repackage logit solver in src/solvers; make pygambit.nash.logit_solve available as a method for finding a Nash equilibrium.

  • Additional game transformation operations have been moved to the Game class, and old versions deprecated.

  • Accessing payoffs of outcomes and pure strategy profiles is now standardized to use player references, and accessing by index has been removed.

  • Game.num_nodes has been removed in favor of Game.nodes, which returns a list of the nodes in the game.

[16.1.0a2] - 2023-09-22#

Changed#

  • Most operations which modify games have been moved to being operations on Game instead of being operations on classes representing elements of games. For the most part old versions have been retained with a deprecation warning; these old versions will be removed in 16.2.0.

  • pygambit.supports has been introduced to organise algorithms which operates on sets of pure strategies or actions, such as finding undominated strategies.

  • .payoff() on mixed strategy and mixed behavior profiles now takes either a Player or string label. .infoset_value() and .action_value() have been introduced to replace calling .payoff() on these objects.

  • The implementation of mixed strategy profiles and mixed behavior profiles has been thoroughly rewritten for improved consistency in behavior across members and between the two types of profile.

  • The experimental concept of a StrategicRestriction has been removed from pygambit. Instead, calling restrict on a StrategySupportProfile creates a deep copy of its game with only the strategies specified.

[16.1.0a1] - 2023-09-14#

Changed#

  • Cython 3.0 is now used for pygambit.

  • Documentation of the pygambit API has been moved into docstrings.

  • Chance action probabilities are now enforced to sum to exactly one at an information set. This is accomplished by changing the API to set probabilities for all actions simultaneously; it is no longer possible to assign an action probability individually.

Added#

  • Documented support in Python for estimating quantal response equilibria using either fixed-point or empirical payoff methods

Fixed#

  • Corrected reference counting for C++ Game objects which could result in objects never being deallocated (see #331)

  • Corrected Lyapunov function minimisation returning critical points that are not global minima (i.e. not equilibria) (#329)

  • Corrected a regression in accessing contingencies of a game in Python.

  • Removed use of explicit StopIteration (a holdover from Python 2.x support).

[16.0.2] - 2022-01-28#

Fixed#

  • Updated build and packaging systems for current compilers across all platforms

  • Refactored Python implementation to make pygambit PyPI-installable