pygambit.nash.logit_solve#
- pygambit.nash.logit_solve(game: Game, use_strategic: bool = False, maxregret: float = 1e-08, first_step: float = 0.03, max_accel: float = 1.1) NashComputationResult #
Compute Nash equilibria of a game using the logit quantal response equilibrium correspondence.
Returns an approximation to the limiting point on the principal branch of the correspondence for the game.
- Parameters:
game (Game) – The game to compute equilibria in.
use_strategic (bool, default False) – Whether to use the strategic form. If True, always uses the strategic representation even if the game’s native representation is extensive.
maxregret (float, default 1e-8) –
The acceptance criterion for approximate Nash equilibrium; the maximum regret of any player must be no more than maxregret times the difference of the maximum and minimum payoffs of the game
New in version 16.2.0.
first_step (float, default .03) –
The arclength of the initial step.
New in version 16.2.0.
max_accel (float, default 1.1) –
The maximum rate at which to lengthen the arclength step size.
New in version 16.2.0.
- Returns:
res – The result represented as a
NashComputationResult
object.- Return type: