def steels_basic_experiment_GG(inc_category_treshold=0.95,
classifier=None,
interaction_type="GG",
beta=1.,
context_size=4,
stimuli=None,
agents=None,
dump_freq=50,
alpha=0.1,
sigma=1.,
num_iter=1000,
topology=None):
classifier, classif_arg = SteelsClassifier, []
#agents = [Agent(SteelsAgentStateWithLexicon(classifier()), SimpleSensor())\
# FIX THIS !!
classif_arg = def_value(classif_arg, [])
for agent in agents:
agent.set_state(SteelsAgentStateWithLexicon(classifier(*classif_arg)))
agent.set_sensor(SimpleSensor())
agent.set_fitness_measure("DG", metrics.get_DS_fitness())
agent.set_fitness_measure("GG", metrics.get_CS_fitness())
AdaptiveNetwork.def_alpha = float(alpha)
AdaptiveNetwork.def_beta = float(beta)
ReactiveUnit.def_sigma = float(sigma)
DiscriminationGame.def_inc_category_treshold = float(inc_category_treshold)
return steels_uniwersal_basic_experiment(num_iter,
agents,
GuessingGame(None, context_size),
topology=topology,
dump_freq=dump_freq,
stimuli=stimuli)
def steels_basic_experiment_GG(inc_category_treshold=0.95, classifier=None,
interaction_type="GG", beta=1., context_size=4, stimuli=None,
agents=None, dump_freq=50, alpha=0.1, sigma=1., num_iter=1000,
topology=None):
classifier, classif_arg = SteelsClassifier, []
#agents = [Agent(SteelsAgentStateWithLexicon(classifier()), SimpleSensor())\
# FIX THIS !!
classif_arg = def_value(classif_arg, [])
for agent in agents:
agent.set_state(SteelsAgentStateWithLexicon(classifier(*classif_arg)))
agent.set_sensor(SimpleSensor())
agent.set_fitness_measure("DG", metrics.get_DS_fitness())
agent.set_fitness_measure("GG", metrics.get_CS_fitness())
AdaptiveNetwork.def_alpha = float(alpha)
AdaptiveNetwork.def_beta = float(beta)
ReactiveUnit.def_sigma = float(sigma)
DiscriminationGame.def_inc_category_treshold = float(inc_category_treshold)
return steels_uniwersal_basic_experiment(num_iter, agents,
GuessingGame(None, context_size), topology=topology,
dump_freq=dump_freq, stimuli=stimuli)
def __init__(self, reactive_units=None, alpha=None, beta=None):
""" Must be with weights !
"""
self.units = def_value(reactive_units, [])
self.alpha = np.longdouble(def_value(alpha, AdaptiveNetwork.def_alpha))
self.beta = np.longdouble(def_value(beta, AdaptiveNetwork.def_beta))
def __init__(self, context_len=4, inc_category_treshold=None):
self.context_len = context_len
self.inc_category_treshold = def_value(inc_category_treshold,
DiscriminationGame.def_inc_category_treshold)
def __init__(self, reactive_units=None, alpha=None, beta=None):
""" Must be with weights !
"""
self.units = def_value(reactive_units, [])
self.alpha = np.longdouble(def_value(alpha, AdaptiveNetwork.def_alpha))
self.beta = np.longdouble(def_value(beta, AdaptiveNetwork.def_beta))
def __init__(self, context_len=4, inc_category_treshold=None):
self.context_len = context_len
self.inc_category_treshold = def_value(
inc_category_treshold,
DiscriminationGame.def_inc_category_treshold)
