def applyEpisodeFinished(self, episodeFinished):
""" apply transformations to episodeFinished and return it. """
DecayExplorer.applyEpisodeFinished(self, episodeFinished)
# at end of episode, randomize the exploration parameters
if episodeFinished:
self.randomizeMapping()
return episodeFinished
def applyEpisodeFinished(self, episodeFinished):
""" apply transformations to episodeFinished and return it. """
episodeFinished = DecayExplorer.applyEpisodeFinished(self, episodeFinished)
if episodeFinished:
if self.oldTable != None:
self.experiment.agent.estimator.values[:] = self.oldTable
self.oldTable = None
return episodeFinished
def __init__(self, epsilon, episodeCount=None, actionCount=None):
""" set the probability epsilon, with which a random action is chosen. """
DecayExplorer.__init__(self, epsilon, episodeCount, actionCount)
def __init__(self, epsilon, episodeCount=None, actionCount=None):
DecayExplorer.__init__(self, epsilon, episodeCount, actionCount)
# active is now property, this is the helper variable
self.active_ = True
self.oldTable = None
def applyState(self, state):
""" save current state for _explore() method later on. """
DecayExplorer.applyState(self, state)
self.state = state
return state
def setExperiment(self, experiment):
DecayExplorer.setExperiment(self, experiment)
# create random exploration mapping
self.explMapping = Linear(self.experiment.conditions['stateDim'], self.experiment.conditions['actionNum'])
self.randomizeMapping()
