class_docstr: This class handles the MCTS tree.
code: def __init__(self, game, nn_agent, args, dirichlet_noise=False):
      self.game = game
      self.nn_agent = nn_agent
      self.args = args
      self.dirichlet_noise = dirichlet_noise
      self.Qsa = {}  # stores Q values for s,a (as defined in the paper)
      self.Nsa = {}  # stores #times edge s,a was visited
      self.Ns = {}  # stores #times board s was visited
      self.Ps = {}  # stores initial policy (returned by neural net)
  
      self.Es = {}  # stores game.getGameEnded ended for board s
      self.Vs = {}
  
file_path: PARL/benchmark/torch/AlphaZero/MCTS.py
imports: import math
  import time
  import numpy
label_desc: Use image node_id 1 to create a new MCTS object  with example: obj = MCTS(game, nn_agent, args, dirichlet_noise)