lagom.envs¶
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class
lagom.envs.
RecordEpisodeStatistics
(env, deque_size=100)[source]¶ -
reset
(**kwargs)[source]¶ Resets the state of the environment and returns an initial observation.
Returns: the initial observation. Return type: observation (object)
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step
(action)[source]¶ Run one timestep of the environment’s dynamics. When end of episode is reached, you are responsible for calling reset() to reset this environment’s state.
Accepts an action and returns a tuple (observation, reward, done, info).
Parameters: action (object) – an action provided by the agent Returns: agent’s observation of the current environment reward (float) : amount of reward returned after previous action done (bool): whether the episode has ended, in which case further step() calls will return undefined results info (dict): contains auxiliary diagnostic information (helpful for debugging, and sometimes learning) Return type: observation (object)
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class
lagom.envs.
NormalizeReward
(env, clip=10.0, gamma=0.99, constant_var=None)[source]¶ -
reset
()[source]¶ Resets the state of the environment and returns an initial observation.
Returns: the initial observation. Return type: observation (object)
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step
(action)[source]¶ Run one timestep of the environment’s dynamics. When end of episode is reached, you are responsible for calling reset() to reset this environment’s state.
Accepts an action and returns a tuple (observation, reward, done, info).
Parameters: action (object) – an action provided by the agent Returns: agent’s observation of the current environment reward (float) : amount of reward returned after previous action done (bool): whether the episode has ended, in which case further step() calls will return undefined results info (dict): contains auxiliary diagnostic information (helpful for debugging, and sometimes learning) Return type: observation (object)
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class
lagom.envs.
TimeStepEnv
(env)[source]¶ -
reset
(**kwargs)[source]¶ Resets the state of the environment and returns an initial observation.
Returns: the initial observation. Return type: observation (object)
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step
(action)[source]¶ Run one timestep of the environment’s dynamics. When end of episode is reached, you are responsible for calling reset() to reset this environment’s state.
Accepts an action and returns a tuple (observation, reward, done, info).
Parameters: action (object) – an action provided by the agent Returns: agent’s observation of the current environment reward (float) : amount of reward returned after previous action done (bool): whether the episode has ended, in which case further step() calls will return undefined results info (dict): contains auxiliary diagnostic information (helpful for debugging, and sometimes learning) Return type: observation (object)
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