Reinforcement Learning, Artificial Intelligence, Machine Learning, Data Science, Statistics.
np.linalg.solve(A, b) 2. bellman equation value = np.zeros((WORLD_SIZE, WORLD_SIZE)) while True: # keep iteration until convergence new_value = np.zeros_like(value) for i in range(WORLD_SIZE): for j in range(WORLD_SIZE): for action in ACTIONS: (next_i, next_j), reward = step([i, j], action) #