RandStrategyThresholdUniform

class poisson_approval.RandStrategyThresholdUniform(profile=None, voting_rule=None, d_ranking_fixed_strategy=None, ratio_optimistic=None)[source]

A random factory of threshold strategies (StrategyThreshold) following the uniform distribution.

Parameters:
  • profile (Profile, optional) –
  • voting_rule (str, optional) – The voting rule. Possible values are APPROVAL, PLURALITY and ANTI_PLURALITY. Default: the same voting rule as profile if a profile is specified, APPROVAL otherwise.
  • d_ranking_fixed_strategy (dict) – Key: ranking. Value: fixed strategy. Cf. examples below.
  • ratio_optimistic (Number, optional) – If specified, it will be applied to all voters, except those in d_ranking_fixed_strategy. If not specified, it depends on profile. If profile is specified and is an instance of ProfileCardinalContinuous, then the ratios of optimistic voters are not mentioned in the strategy (because they are useless). In other cases, they are drawn at random.

Examples

Basic usage:

>>> initialize_random_seeds()
>>> rand_strategy = RandStrategyThresholdUniform()
>>> strategy = rand_strategy()
>>> print(strategy)
<abc: utility-dependent (0.5488135039273248, 0.7151893663724195), acb: utility-dependent (0.6027633760716439, 0.5448831829968969), bac: utility-dependent (0.4236547993389047, 0.6458941130666561), bca: utility-dependent (0.4375872112626925, 0.8917730007820798), cab: utility-dependent (0.9636627605010293, 0.3834415188257777), cba: utility-dependent (0.7917250380826646, 0.5288949197529045)>

Specify a profile:

>>> from poisson_approval import ProfileHistogram
>>> profile = ProfileHistogram({'abc': 0.75, 'bac': 0.25}, {'abc': [1], 'bac': [1]})
>>> rand_strategy = RandStrategyThresholdUniform(profile=profile)
>>> strategy = rand_strategy()
>>> print(strategy)
<abc: utility-dependent (0.5680445610939323), bac: utility-dependent (0.925596638292661)> ==> a

Specify some fixed strategies:

>>> rand_strategy = RandStrategyThresholdUniform(
...     d_ranking_fixed_strategy={'abc': 1, 'acb': 1, 'bac': 1, 'bca': (0.5, 0.5)})
>>> print(rand_strategy())
<abc: a, acb: a, bac: b, bca: utility-dependent (0.5, 0.5), cab: utility-dependent (0.07103605819788694, 0.08712929970154071), cba: utility-dependent (0.02021839744032572, 0.832619845547938)>

Give the ratio of optimistic voters explicitly:

>>> rand_strategy = RandStrategyThresholdUniform(
...     d_ranking_fixed_strategy={'abc': 1, 'acb': 1, 'bac': 1, 'bca': 1},
...     ratio_optimistic=0.42)
>>> print(rand_strategy())
<abc: a, acb: a, bac: b, bca: b, cab: utility-dependent (0.7781567509498505, 0.42), cba: utility-dependent (0.8700121482468192, 0.42)>