def METHOD_NAME():
    old_behaviors = yaml.safe_load(PPO_CONFIG)
    old_curriculum = yaml.safe_load(CURRICULUM)
    old_sampler = yaml.safe_load(RANDOMIZATION)
    config = convert(old_behaviors, old_curriculum, old_sampler)
    assert BRAIN_NAME in config["behaviors"]
    assert "big_wall_min_height" in config["environment_parameters"]
    curriculum = config["environment_parameters"]["big_wall_min_height"]["curriculum"]
    assert len(curriculum) == 4
    for i, expected_value in enumerate([0.0, 4.0, 6.0, 8.0]):
        assert curriculum[i][f"Lesson{i}"]["value"] == expected_value
    for i, threshold in enumerate([0.1, 0.3, 0.5]):
        criteria = curriculum[i][f"Lesson{i}"]["completion_criteria"]
        assert criteria["threshold"] == threshold
        assert criteria["behavior"] == "BigWallJump"
        assert criteria["signal_smoothing"]
        assert criteria["min_lesson_length"] == 200
        assert criteria["measure"] == "progress"
    assert "gravity" in config["environment_parameters"]
    gravity = config["environment_parameters"]["gravity"]
    assert gravity["sampler_type"] == "uniform"
    assert gravity["sampler_parameters"]["min_value"] == 7
    assert gravity["sampler_parameters"]["max_value"] == 12