def initialize_P(nS, nA):
    """Initializes a uniformly random model of the environment with 0 rewards.

    Parameters
    ----------
    nS: int
        Number of states
    nA: int
        Number of actions

    Returns
    -------
    P: np.array of shape [nS x nA x nS x 4] where items are tuples representing transition information
        P[state][action] is a list of (prob, next_state, reward, done) tuples.
    """
    P = [[[(1.0/nS, i, 0, False) for i in range(nS)] for _ in range(nA)] for _ in range(nS)]

    return P