lagom.envs

class lagom.envs.RecordEpisodeStatistics(env, deque_size=100)

reset(**kwargs)

Resets the state of the environment and returns an initial observation.

Returns:the initial observation. Return type:observation (object)

step(action)

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)

class lagom.envs.NormalizeObservation(env, clip=5.0, constant_moments=None)

class lagom.envs.NormalizeReward(env, clip=10.0, gamma=0.99, constant_var=None)

reset()

Resets the state of the environment and returns an initial observation.

Returns:the initial observation. Return type:observation (object)

step(action)

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)

class lagom.envs.TimeStepEnv(env)

reset(**kwargs)

Resets the state of the environment and returns an initial observation.

Returns:the initial observation. Return type:observation (object)

step(action)

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)