Probability, Python, Games, Markov Chains, Data Science.
transition_matrix = np.zeros((num_states, num_states)) for i in range(num_states): for j in range(num_states): transition_matrix[i][j] = compute_transition_probability(i, j) transition_matrix[i][num_states-1] = 1 - transition_matrix[i][:num_states-1].sum() assert