class_docstr: Implement the epsilon greedy policy
  
  Eps Greedy policy either:
  
  - takes a random action with probability epsilon
  - takes current best action with prob (1 - epsilon)
class_docstr_tok: ["Implement","the","epsilon","greedy","policy","Eps","Greedy","policy","either",":","-","takes","a","random","action","with","probability","epsilon","-","takes","current","best","action","with","prob","(","1","-","epsilon",")"]
code: def __init__(self, eps=0.1):
      super(EpsGreedyQPolicy, self).__init__()
      self.eps = eps
  
imports: from __future__ import division
  import numpy
  from rl.util import *
label_desc: Use image node_id 1 to create a new EpsGreedyQPolicy object from inherited base classes: Policy with example: obj = EpsGreedyQPolicy(eps)