garage.np.policies.scripted_policy
¶
Simulates a garage policy object.
- class ScriptedPolicy(scripted_actions, agent_env_infos=None)[source]¶
Bases:
garage.np.policies.policy.Policy
Simulates a garage policy object.
- Parameters
- property env_spec¶
Policy environment specification.
- Returns
Environment specification.
- Return type
- property observation_space¶
Observation space.
- Returns
The observation space of the environment.
- Return type
akro.Space
- property action_space¶
Action space.
- Returns
The action space of the environment.
- Return type
akro.Space
- set_param_values(params)[source]¶
Set param values.
- Parameters
params (np.ndarray) – A numpy array of parameter values.
- get_param_values()[source]¶
Get param values.
- Returns
- Values of the parameters evaluated in
the current session
- Return type
np.ndarray
- get_action(observation)[source]¶
Return a single action.
- Parameters
observation (numpy.ndarray) – Observations.
- Returns
Action given input observation. dict[dict]: Agent infos indexed by observation.
- Return type
- reset(do_resets=None)¶
Reset the policy.
This is effective only to recurrent policies.
do_resets is an array of boolean indicating which internal states to be reset. The length of do_resets should be equal to the length of inputs, i.e. batch size.
- Parameters
do_resets (numpy.ndarray) – Bool array indicating which states to be reset.