`garage.np.exploration_policies.add_gaussian_noise`¶

Gaussian exploration strategy.

class AddGaussianNoise(env_spec, policy, max_sigma=1.0, min_sigma=0.1, decay_period=1000000)¶

Add Gaussian noise to the action taken by the deterministic policy.

Parameters:

env_spec (EnvSpec) – Environment spec to explore.
policy (garage.Policy) – Policy to wrap.
max_sigma (float) – Action noise standard deviation at the start of exploration.
min_sigma (float) – Action noise standard deviation at the end of the decay period.
decay_period (int) – Number of episodes over which to linearly decay sigma from max_sigma to min_sigma.

reset(self, dones=None)¶

Reset the state of the exploration.

Parameters:	dones (List[bool] or numpy.ndarray or None) – Which vectorization states to reset.

get_action(self, observation)¶

Get action from this policy for the input observation.

Parameters:	observation (numpy.ndarray) – Observation from the environment.
Returns:	Actions with noise. List[dict]: Arbitrary policy state information (agent_info).
Return type:	np.ndarray

get_actions(self, observations)¶

Get actions from this policy for the input observation.

Parameters:	observations (list) – Observations from the environment.
Returns:	Actions with noise. List[dict]: Arbitrary policy state information (agent_info).
Return type:	np.ndarray

get_param_values(self)¶

Get parameter values.

Returns:	Values of each parameter.
Return type:	list or dict

set_param_values(self, params)¶

Set param values.

Parameters:	params (np.ndarray) – A numpy array of parameter values.

garage.np.exploration_policies.add_gaussian_noise¶