""" Example of using MMD with dilated entropy
    to solve for QRE in a Matrix Game """

from absl import app
from absl import flags

from open_spiel.python.algorithms import mmd_dilated
import pyspiel

FLAGS = flags.FLAGS

flags.DEFINE_integer("iterations", 1000, "Number of iterations")
flags.DEFINE_float("alpha", 0.1, "QRE parameter, larger value amounts to more regularization")
flags.DEFINE_integer("print_freq", 100, "How often to print the gap")

# create pyspiel perturbed RPS matrix game

game = pyspiel.create_matrix_game([[0, -1, 3],
                                   [1, 0, -3],
                                   [-3, 3, 0]],
                                  [[0, 1, -3],
                                   [-1, 0, 3],
                                   [3, -3, 0]])

game = pyspiel.convert_to_turn_based(game)

def main(_):
  mmd = mmd_dilated.MMDDilatedEnt(game, FLAGS.alpha)
  for i in range(FLAGS.iterations):
    mmd.update_sequences()
    if i % FLAGS.print_freq == 0:
      conv = mmd.get_gap()
      print("Iteration {} gap {}".format(i, conv))

  # Extract policies for both players
  print(mmd.get_policies().action_probability_array)
  # Note the sequence form and behavioural-form coincide
  # for a normal-form game (sequence form has extra root value of 1)
  print(mmd.current_sequences())

if __name__ == "__main__":
  app.run(main)
add mmd matrix example