egttools.behaviors.NormalForm.TwoActions.GenerousTFT

class GenerousTFT(self: egttools.numerical.numerical_.behaviors.NormalForm.TwoActions.GenerousTFT, R: SupportsFloat | SupportsIndex, P: SupportsFloat | SupportsIndex, T: SupportsFloat | SupportsIndex, S: SupportsFloat | SupportsIndex)

Bases: AbstractNFGStrategy

Generous Tit for Tat.

Construct a Generous Tit for Tat strategy.

Following a defection, the strategy cooperates with probability

p(R, P, T, S) = min(1 - (T - R) / (R - S), (R - P) / (T - P))

where R, P, T, and S are the reward, punishment, temptation, and sucker’s payoff.

Parameters:

  • R (float) – Reward payoff.

  • P (float) – Punishment payoff.

  • T (float) – Temptation payoff.

  • S (float) – Sucker’s payoff.

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.GenerousTFT, R: SupportsFloat | SupportsIndex, P: SupportsFloat | SupportsIndex, T: SupportsFloat | SupportsIndex, S: SupportsFloat | SupportsIndex) → None

Construct a Generous Tit for Tat strategy.

Following a defection, the strategy cooperates with probability

p(R, P, T, S) = min(1 - (T - R) / (R - S), (R - P) / (T - P))

where R, P, T, and S are the reward, punishment, temptation, and sucker’s payoff.

Parameters:

  • R (float) – Reward payoff.

  • P (float) – Punishment payoff.

  • T (float) – Temptation payoff.

  • S (float) – Sucker’s payoff.

__new__(**kwargs)
get_action(self: egttools.numerical.numerical_.behaviors.NormalForm.TwoActions.GenerousTFT, 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.GenerousTFT) → bool

Return whether the strategy is stochastic.

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

Return the strategy type.

__annotations__ = {}