code: def rlmf_tictactoe():
    
    hparams = rlmf_original()
    hparams.game = "tictactoe"
    hparams.rl_env_name = "T2TEnv-TicTacToeEnv-v0"
    # Since we don't have any no-op actions, otherwise we have to have an
    # attribute called `get_action_meanings`.
    hparams.eval_max_num_noops = 0
    hparams.max_num_noops = 0
    hparams.rl_should_derive_observation_space = False
  
    hparams.policy_network = "feed_forward_categorical_policy"
    hparams.base_algo_params = "ppo_ttt_params"
  
    # Number of last observations to feed to the agent
    hparams.frame_stack_size = 1
    return hparams
docs: Base set of hparams for model-free PPO.