class_docstr: A combination of the eps-greedy and Boltzman q-policy.
  
  Wiering, M.: Explorations in Efficient Reinforcement Learning.
  PhD thesis, University of Amsterdam, Amsterdam (1999)
  
  https://pure.uva.nl/ws/files/3153478/8461_UBA003000033.pdf
class_docstr_tok: ["A","combination","of","the","eps-greedy","and","Boltzman","q-policy",".","Wiering",",","M.",":","Explorations","in","Efficient","Reinforcement","Learning",".","PhD","thesis",",","University","of","Amsterdam",",","Amsterdam","(","1999",")","https",":","\/\/pure.uva.nl\/ws\/files\/3153478\/8461_UBA003000033.pdf"]
docstr: Return configurations of MaxBoltzmannQPolicy
  
  # Returns
      Dict of config
code: def get_config(self):
      """Return configurations of MaxBoltzmannQPolicy
  
      # Returns
          Dict of config
      """
      config = super(MaxBoltzmannQPolicy, self).get_config()
      config["eps"] = self.eps
      config["tau"] = self.tau
      config["clip"] = self.clip
      return config
  
imports: from __future__ import division
  import numpy
  from rl.util import *
label_desc: Use image node_id 3 for calling the MaxBoltzmannQPolicy obj's underlying member method code with example usage: obj.get_config() and returns: config