本文整理汇总了Python中pybrain.rl.environments.episodic.EpisodicTask.__init__方法的典型用法代码示例。如果您正苦于以下问题：Python EpisodicTask.__init__方法的具体用法？Python EpisodicTask.__init__怎么用？Python EpisodicTask.__init__使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类pybrain.rl.environments.episodic.EpisodicTask的用法示例。
在下文中一共展示了EpisodicTask.__init__方法的5个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: __init__
# 需要导入模块: from pybrain.rl.environments.episodic import EpisodicTask [as 别名]
# 或者: from pybrain.rl.environments.episodic.EpisodicTask import __init__ [as 别名]
def __init__(self, env, episodeLength):
EpisodicTask.__init__(self, env)
#self.inDim = 1
#self.outDim = 1
self.counter = 0
self.history = []
self.total = []
self.episodeLength = episodeLength示例2: __init__
# 需要导入模块: from pybrain.rl.environments.episodic import EpisodicTask [as 别名]
# 或者: from pybrain.rl.environments.episodic.EpisodicTask import __init__ [as 别名]
def __init__(self, environment):
'''
Constructor
'''
EpisodicTask.__init__(self, environment)
self.prev_time = 0
self.current_time = 0
self.reward = 0示例3: __init__
# 需要导入模块: from pybrain.rl.environments.episodic import EpisodicTask [as 别名]
# 或者: from pybrain.rl.environments.episodic.EpisodicTask import __init__ [as 别名]
def __init__(self, size, opponent = None, **args):
EpisodicTask.__init__(self, PenteGame((size, size)))
self.setArgs(**args)
if opponent == None:
opponent = RandomGomokuPlayer(self.env)
elif isclass(opponent):
# assume the agent can be initialized without arguments then.
opponent = opponent(self.env)
if not self.opponentStart:
opponent.color = PenteGame.WHITE
self.opponent = opponent
self.minmoves = 9
self.maxmoves = self.env.size[0] * self.env.size[1]
self.reset()示例4: __init__
# 需要导入模块: from pybrain.rl.environments.episodic import EpisodicTask [as 别名]
# 或者: from pybrain.rl.environments.episodic.EpisodicTask import __init__ [as 别名]
def __init__(self, size, opponent = None, **args):
EpisodicTask.__init__(self, CaptureGame(size))
self.setArgs(**args)
if opponent == None:
opponent = RandomCapturePlayer(self.env)
elif isclass(opponent):
# assume the agent can be initialized without arguments then.
opponent = opponent(self.env)
else:
opponent.game = self.env
if not self.opponentStart:
opponent.color = CaptureGame.WHITE
self.opponent = opponent
self.maxmoves = self.env.size * self.env.size
self.minmoves = 3
self.reset()示例5: __init__
# 需要导入模块: from pybrain.rl.environments.episodic import EpisodicTask [as 别名]
# 或者: from pybrain.rl.environments.episodic.EpisodicTask import __init__ [as 别名]
def __init__(self,
environment,
deltaP,
deltaF,
deltaS,
discount,
backtest=False):
""" Standard constructor for the asset allocation task.
Args:
environment (Environment): market environment object
deltaP (double): proportional transaction costs rate
deltaF (double): fixed transaction cost rate
deltaS (double): short selling borrowing cost rate
discount (double): discount factor
backtest (bool): flag for training mode or test mode
"""
# Initialize episodic task
EpisodicTask.__init__(self, environment)
# Transaction costs
self.deltaP = deltaP
self.deltaF = deltaF
self.deltaS = deltaS
# Discount factor
self.discount = discount
# Backtesting
self.backtest = backtest
# Report stores allocations and portfolio log-returns for backtesting
self.report = pd.DataFrame(columns=list(self.env.data.columns) +
['ptfLogReturn'])
# Initialize allocation
self.initializeAllocation()