egttools.behaviors.CRD.CRDMemoryOnePlayer

class CRDMemoryOnePlayer(self: egttools.numerical.numerical_.behaviors.CRD.CRDMemoryOnePlayer, personal_threshold: SupportsInt | SupportsIndex, initial_action: SupportsInt | SupportsIndex, action_above: SupportsInt | SupportsIndex, action_equal: SupportsInt | SupportsIndex, action_below: SupportsInt | SupportsIndex)

Bases: AbstractCRDStrategy

Memory-one strategy for collective-risk dilemma games.

Construct a memory-one strategy for a collective-risk dilemma.

The strategy contributes initial_action in the first round. In later rounds, it compares the sum of contributions of the other group members in the previous round to personal_threshold.

  • if the previous group contribution is greater than personal_threshold, the player chooses action_above;

  • if it is equal to personal_threshold, the player chooses action_equal;

  • if it is smaller than personal_threshold, the player chooses action_below.

Parameters:

  • personal_threshold (int) – Threshold against which the previous group contribution is compared.

  • initial_action (int) – Contribution in the first round.

  • action_above (int) – Contribution used when the previous group contribution is above the threshold.

  • action_equal (int) – Contribution used when the previous group contribution equals the threshold.

  • action_below (int) – Contribution used when the previous group contribution is below the threshold.

See also

egttools.behaviors.CRD.AbstractCRDStrategy, egttools.games.CRDGame, egttools.games.CRDGameTU

Methods

get_action

Return the action chosen by the strategy.

type

Return the strategy type.
__init__(self: egttools.numerical.numerical_.behaviors.CRD.CRDMemoryOnePlayer, personal_threshold: SupportsInt | SupportsIndex, initial_action: SupportsInt | SupportsIndex, action_above: SupportsInt | SupportsIndex, action_equal: SupportsInt | SupportsIndex, action_below: SupportsInt | SupportsIndex) → None

Construct a memory-one strategy for a collective-risk dilemma.

The strategy contributes initial_action in the first round. In later rounds, it compares the sum of contributions of the other group members in the previous round to personal_threshold.

  • if the previous group contribution is greater than personal_threshold, the player chooses action_above;

  • if it is equal to personal_threshold, the player chooses action_equal;

  • if it is smaller than personal_threshold, the player chooses action_below.

Parameters:

  • personal_threshold (int) – Threshold against which the previous group contribution is compared.

  • initial_action (int) – Contribution in the first round.

  • action_above (int) – Contribution used when the previous group contribution is above the threshold.

  • action_equal (int) – Contribution used when the previous group contribution equals the threshold.

  • action_below (int) – Contribution used when the previous group contribution is below the threshold.

See also

egttools.behaviors.CRD.AbstractCRDStrategy, egttools.games.CRDGame, egttools.games.CRDGameTU

__new__(**kwargs)
__str__(self: egttools.numerical.numerical_.behaviors.CRD.CRDMemoryOnePlayer) → str
get_action(self: egttools.numerical.numerical_.behaviors.CRD.CRDMemoryOnePlayer, time_step: SupportsInt | SupportsIndex, group_contributions_prev: SupportsInt | SupportsIndex) → int

Return the action chosen by the strategy.

Parameters:

  • time_step (int) – Current round.

  • group_contributions_prev (int) – Sum of contributions of the other group members in the previous round.

Returns:

Action selected by the strategy.

Return type:

int

Examples

>>> from egttools.behaviors.CRD import CRDMemoryOnePlayer
>>> strategy = CRDMemoryOnePlayer(4, 2, 4, 2, 0)
>>> strategy.get_action(0, 0)
2
type(self: egttools.numerical.numerical_.behaviors.CRD.CRDMemoryOnePlayer) → str

Return the strategy type.

__annotations__ = {}