parameters: (self,
                 game,
                 state_value: Optional[value.ValueFunction] = None,
                 lr=0.01,
                 root_state=None)
docstring: Initializes mirror descent.
  
      Args:
        game: The game,
        state_value: A state value function. Default to TabularValueFunction.
        lr: The learning rate of mirror descent,
        root_state: The state of the game at which to start. If `None`, the game
          root state is used.
docstring_summary: Initializes mirror descent.
docstring_tokens: Initializes mirror descent .
function: def __init__(self,
                 game,
                 state_value: Optional[value.ValueFunction] = None,
                 lr=0.01,
                 root_state=None):
      """Initializes mirror descent.
  
      Args:
        game: The game,
        state_value: A state value function. Default to TabularValueFunction.
        lr: The learning rate of mirror descent,
        root_state: The state of the game at which to start. If `None`, the game
          root state is used.
      """
      self._game = game
      if root_state is None:
        self._root_states = game.new_initial_states()
      else:
        self._root_states = [root_state]
      self._policy = policy_std.UniformRandomPolicy(game)
      self._distribution = distribution.DistributionPolicy(game, self._policy)
      self._md_step = 0
      self._lr = lr
  
      self._state_value = (state_value if state_value
                           else value.TabularValueFunction(game))
      self._cumulative_state_value = value.TabularValueFunction(game)
function_tokens: def __init__ ( self , game , state_value : Optional [ value . ValueFunction ] = None , lr = 0.01 , root_state = None ) : self . _game = game if root_state is None : self . _root_states = game . new_initial_states ( ) else : self . _root_states = [ root_state ] self . _policy = policy_std . UniformRandomPolicy ( game ) self . _distribution = distribution . DistributionPolicy ( game , self . _policy ) self . _md_step = 0 self . _lr = lr self . _state_value = ( state_value if state_value else value . TabularValueFunction ( game ) ) self . _cumulative_state_value = value . TabularValueFunction ( game )