text: import numpy as np  # linear algebra
  import pandas as pd  # data processing, CSV file I/O (e.g. pd.read_csv)
  import matplotlib.pyplot as plt
  import os
  
  from RLC.real_chess import agent, environment, learn, tree
  import chess
  from chess.pgn import Game
  
  opponent = agent.GreedyAgent()
  env = environment.Board(opponent, FEN=None)
  player = agent.Agent(lr=0.01, network='big')
  learner = learn.TD_search(env, player, gamma=0.8, search_time=2)
  node = tree.Node(learner.env.board, gamma=learner.gamma)
  player.model.summary()
  
  learner.learn(iters=1000, timelimit_seconds=3600)
  
  reward_smooth = pd.DataFrame(learner.reward_trace)
  reward_smooth.rolling(window=500, min_periods=0).mean().plot(figsize=(16, 9),
                                                               title='average performance over the last 3 episodes')
  plt.show()
  
  reward_smooth = pd.DataFrame(learner.piece_balance_trace)
  reward_smooth.rolling(window=100, min_periods=0).mean().plot(figsize=(16, 9),
                                                               title='average piece balance over the last 3 episodes')
  plt.show()
  
  pgn = Game.from_board(learner.env.board)
  with open("rlc_pgn", "w") as log:
      log.write(str(pgn))
  