garage.np.baselines

Baselines (value functions) which use NumPy as a numerical backend.

class Baseline

Bases: abc.ABC

Inheritance diagram of garage.np.baselines.Baseline

Base class for all baselines.

fit(self, paths)

Fit regressor based on paths.

Parameters:paths (dict[numpy.ndarray]) – Sample paths.
predict(self, paths)

Predict value based on paths.

Parameters:paths (dict[numpy.ndarray]) – Sample paths.
Returns:Predicted value.
Return type:numpy.ndarray
class LinearFeatureBaseline(env_spec, reg_coeff=1e-05, name='LinearFeatureBaseline')

Bases: garage.np.baselines.baseline.Baseline

Inheritance diagram of garage.np.baselines.LinearFeatureBaseline

A linear value function (baseline) based on features.

Parameters:
  • env_spec (garage.envs.env_spec.EnvSpec) – Environment specification.
  • reg_coeff (float) – Regularization coefficient.
  • name (str) – Name of baseline.
get_param_values(self)

Get parameter values.

Returns:A list of values of each parameter.
Return type:List[np.ndarray]
set_param_values(self, flattened_params)

Set param values.

Parameters:flattened_params (np.ndarray) – A numpy array of parameter values.
fit(self, paths)

Fit regressor based on paths.

Parameters:paths (list[dict]) – Sample paths.
predict(self, paths)

Predict value based on paths.

Parameters:paths (list[dict]) – Sample paths.
Returns:Predicted value.
Return type:numpy.ndarray
class LinearMultiFeatureBaseline(env_spec, features=None, reg_coeff=1e-05, name='LinearMultiFeatureBaseline')

Bases: garage.np.baselines.LinearFeatureBaseline

Inheritance diagram of garage.np.baselines.LinearMultiFeatureBaseline

A linear value function (baseline) based on features.

Parameters:
  • env_spec (garage.envs.env_spec.EnvSpec) – Environment specification.
  • reg_coeff (float) – Regularization coefficient.
  • features (list[str]) – Name of features.
  • name (str) – Name of baseline.
get_param_values(self)

Get parameter values.

Returns:A list of values of each parameter.
Return type:List[np.ndarray]
set_param_values(self, flattened_params)

Set param values.

Parameters:flattened_params (np.ndarray) – A numpy array of parameter values.
fit(self, paths)

Fit regressor based on paths.

Parameters:paths (list[dict]) – Sample paths.
predict(self, paths)

Predict value based on paths.

Parameters:paths (list[dict]) – Sample paths.
Returns:Predicted value.
Return type:numpy.ndarray
class ZeroBaseline(env_spec)

Bases: garage.np.baselines.baseline.Baseline

Inheritance diagram of garage.np.baselines.ZeroBaseline

Base class for all baselines.

get_param_values(self, **kwargs)
set_param_values(self, val, **kwargs)
fit(self, paths)

Fit regressor based on paths.

Parameters:paths (dict[numpy.ndarray]) – Sample paths.
predict(self, path)

Predict value based on paths.

Parameters:paths (dict[numpy.ndarray]) – Sample paths.
Returns:Predicted value.
Return type:numpy.ndarray
predict_n(self, paths)