egttools.behaviors.NormalForm.TwoActions.GradualTFT

class GradualTFT(self: egttools.numerical.numerical_.behaviors.NormalForm.TwoActions.GradualTFT)

Bases: AbstractNFGStrategy

Gradual Tit for Tat.

Tit for Tat with two modifications:

  1. The number of punishing defections increases with each additional defection by the opponent.

  2. After each punishment phase, the strategy apologizes by cooperating in the following two rounds.

Methods

get_action

Return the action chosen by the strategy.

is_stochastic

Return whether the strategy is stochastic.

type

Return the strategy type.
__init__(self: egttools.numerical.numerical_.behaviors.NormalForm.TwoActions.GradualTFT) → None

Tit for Tat with two modifications:

  1. The number of punishing defections increases with each additional defection by the opponent.

  2. After each punishment phase, the strategy apologizes by cooperating in the following two rounds.

__new__(**kwargs)
get_action(self: egttools.numerical.numerical_.behaviors.NormalForm.TwoActions.GradualTFT, time_step: SupportsInt | SupportsIndex, action_prev: SupportsInt | SupportsIndex) → int

Return the action chosen by the strategy.

Parameters:

  • time_step (int) – Current round.

  • action_prev (int) – Previous action of the opponent.

Returns:

Action selected by the strategy.

Return type:

int

is_stochastic(self: egttools.numerical.numerical_.behaviors.NormalForm.TwoActions.GradualTFT) → bool

Return whether the strategy is stochastic.

type(self: egttools.numerical.numerical_.behaviors.NormalForm.TwoActions.GradualTFT) → str

Return the strategy type.

__annotations__ = {}