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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

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.

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

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

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

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

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

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

The first alpha release for 16.1.0.