def __init__(self, learner, sdim, adim=1, maxHistoryLength=1000,
batch=False):
LoggingAgent.__init__(self, sdim, adim)
self.learner = learner
self.policy = self.learner.module.policy
self.lastaction = None
self.learning = True
self.batch = batch
self.currentDataIndex = 0
self.maxHistoryLength = maxHistoryLength
def __init__(self, learner, **kwargs):
LoggingAgent.__init__(self,learner.num_features,learner.num_actions, **kwargs)
self.learner = learner
self.reset()
self.learning=True
self.learner.dataset=self.history
self.visited_states_x=[]
self.visited_states_y=[]
self.qvalues=[]
self.actionvalues=[]
self.init_exploration=1.0
def __init__(self, module, learner = None):
"""
:key module: the acting module
:key learner: the learner (optional) """
LoggingAgent.__init__(self, module.indim, module.outdim)
self.module = module
self.learner = learner
# if learner is available, tell it the module and data
if self.learner is not None:
self.learner.module = self.module
self.learner.dataset = self.history
self.learning = True
def __init__(self, learner, **kwargs):
LoggingAgent.__init__(self, learner.num_features, 1, **kwargs)
self.learner = learner
self.learner._behaviorPolicy = self._actionProbs
self.reset()
def __init__(self, learner, **kwargs):
LoggingAgent.__init__(self,2,1, **kwargs)
self.learner = learner
#self.reset()
self.learning=True
self.learner.dataset=self.history
