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ChangeLog
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ChangeLog
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# Changelog
## [16.2.0] - unreleased
### 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