old_contents: import random
  
  
  class TabularF(dict):
      '''
      Tabular representation for any of the two types of value functions:
  
      1. state value function (V-Functions).
         e.g.
         vf = TabularF()
         vf[state] = 1
  
      2. state-action value functions (Q-functions)
         e.g.
         qf = TabularF()
         qf[(state, action)] = 1
  
      '''
  
      def __getitem__(self, key):
          if key not in self:
              self[key] = random.random() - 0.5
          return super(TabularF, self).__getitem__(key)
  
new_contents: import random
  
  _MEAN = 0.0
  _STD = 0.3
  
  class TabularF(dict):
      '''
      Tabular representation for any of the two types of value functions:
  
      1. state value function (V-Functions).
         e.g.
         vf = TabularF()
         vf[state] = 1
  
      2. state-action value functions (Q-functions)
         e.g.
         qf = TabularF()
         qf[(state, action)] = 1
  
      '''
  
      def __getitem__(self, key):
          if key not in self:
              self[key] = random.gauss(_MEAN, _STD)
          return super(TabularF, self).__getitem__(key)
  
subject: Initialize values using a gaussian distribution with mean = 0 and std = 0.3