class_docstr: Add Gaussian noise to the action taken by the deterministic policy.
  
  Args:
      env_spec (EnvSpec): Environment spec to explore.
      policy (garage.Policy): Policy to wrap.
      total_timesteps (int): Total steps in the training, equivalent to
          max_episode_length * n_epochs.
      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_ratio (float): Fraction of total steps for epsilon decay.
class_docstr_tok: ["Add","Gaussian","noise","to","the","action","taken","by","the","deterministic","policy",".","Args",":","env_spec","(","EnvSpec",")",":","Environment","spec","to","explore",".","policy","(","garage.Policy",")",":","Policy","to","wrap",".","total_timesteps","(","int",")",":","Total","steps","in","the","training",",","equivalent","to","max_episode_length","*","n_epochs",".","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_ratio","(","float",")",":","Fraction","of","total","steps","for","epsilon","decay","."]
docstr: Update the exploration policy using a batch of trajectories.
  
  Args:
      episode_batch (EpisodeBatch): A batch of trajectories which
          were sampled with this policy active.
docstr_tok: ["Update","the","exploration","policy","using","a","batch","of","trajectories",".","Args",":","episode_batch","(","EpisodeBatch",")",":","A","batch","of","trajectories","which","were","sampled","with","this","policy","active","."]
code: def update(self, episode_batch):
      """Update the exploration policy using a batch of trajectories.
  
      Args:
          episode_batch (EpisodeBatch): A batch of trajectories which
              were sampled with this policy active.
  
      """
      self._total_env_steps = self._last_total_env_steps + np.sum(
          episode_batch.lengths
      )
      self._last_total_env_steps = self._total_env_steps
      tabular.record("AddGaussianNoise/Sigma", self._sigma())
  
file_path: garage/src/garage/np/exploration_policies/add_gaussian_noise.py
imports: import akro
  from dowel import tabular
  import numpy
  from garage.np.exploration_policies.exploration_policy import ExplorationPolicy
label_desc: Use image node_id 5 for calling the AddGaussianNoise obj's underlying member method code with example usage: obj.update(episode_batch) without return types