Version 16.2.0

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

Version 16.1.1

The stable release of version 16.1.1.

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.

Version 16.1.0

The stable release of version 16.1.0. See ChangeLog for what's new.

Version 16.1.0b1

The first beta release in preparation for Version 16.1.0. See ChangeLog for what's new.

Version 16.1.0a4

The fourth alpha release in preparation for Version 16.1.0. See ChangeLog for what's new.

Version 16.1.0a3

The third alpha release in preparation for Version 16.1.0. See ChangeLog for what's new.

Version 16.1.0a2

The second alpha release in preparation for Version 16.1.0. See ChangeLog for what's new.

Version 16.1.0a1

The first alpha release for 16.1.0.

Version 16.0.2

This is a retroactive mirror of the files for 16.0.2 (which were originally released on Sourceforge).