class_docstr: Additive Ornstein-Uhlenbeck process.
  
  Used in https://arxiv.org/abs/1509.02971 for exploration.
  
  Args:
      mu (float): Mean of the OU process
      theta (float): Friction to pull towards the mean
      sigma (float or ndarray): Scale of noise
      start_with_mu (bool): Start the process without noise
code: def __repr__(self):
      return "AdditiveOU(mu={}, theta={}, sigma={})".format(
          self.mu, self.theta, self.sigma
      )
  
file_path: chainerrl/chainerrl/explorers/additive_ou.py
imports: from logging import getLogger
  import numpy
  from chainerrl import explorer
label_desc: Use image node_id 4 for calling the AdditiveOU obj's underlying member method code with example usage: obj.__repr__() and returns: str