Releases · gambitproject/gambit

05 Apr 10:46

tturocy

v16.2.0

b19c549

Version 16.2.0 Latest

Latest

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

Assets 5

10 Jan 09:42

tturocy

v16.1.1

a7f0754

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.

Assets 5