garage.torch.policies.discrete_qf_argmax_policy
¶
A Discrete QFunction-derived policy.
This policy chooses the action that yields to the largest Q-value.
-
class
DiscreteQFArgmaxPolicy
(qf, env_spec, name='DiscreteQFArgmaxPolicy')¶ Bases:
garage.torch.policies.policy.Policy
Policy that derives its actions from a learned Q function.
The action returned is the one that yields the highest Q value for a given state, as determined by the supplied Q function.
- Parameters
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forward
(self, observations)¶ Get actions corresponding to a batch of observations.
- Parameters
observations (torch.Tensor) – Batch of observations of shape \((N, O)\). Observations should be flattened even if they are images as the underlying Q network handles unflattening.
- Returns
Batch of actions of shape \((N, A)\)
- Return type
torch.Tensor
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get_action
(self, observation)¶ Get a single action given an observation.
- Parameters
observation (np.ndarray) – Observation with shape \((O, )\).
- Returns
Predicted action with shape \((A, )\). dict: Empty since this policy does not produce a distribution.
- Return type
torch.Tensor
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get_actions
(self, observations)¶ Get actions given observations.
- Parameters
observations (np.ndarray) – Batch of observations, should have shape \((N, O)\).
- Returns
Predicted actions. Tensor has shape \((N, A)\). dict: Empty since this policy does not produce a distribution.
- Return type
torch.Tensor
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get_param_values
(self)¶ Get the parameters to the policy.
This method is included to ensure consistency with TF policies.
- Returns
The parameters (in the form of the state dictionary).
- Return type
-
set_param_values
(self, state_dict)¶ Set the parameters to the policy.
This method is included to ensure consistency with TF policies.
- Parameters
state_dict (dict) – State dictionary.
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reset
(self, 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.
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property
env_spec
(self)¶ Policy environment specification.
- Returns
Environment specification.
- Return type
garage.EnvSpec
-
property
observation_space
(self)¶ Observation space.
- Returns
The observation space of the environment.
- Return type
akro.Space
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property
action_space
(self)¶ Action space.
- Returns
The action space of the environment.
- Return type
akro.Space