We want to apply the policy iteration algorithm in order to find an optimal policy for the tunnel environment. Let's start by defining a random initial policy and a value matrix with all values (except the terminal states) equal to 0:
import numpy as npnb_actions = 4policy = np.random.randint(0, nb_actions, size=(height, width)).astype(np.uint8)tunnel_values = np.zeros(shape=(height, width))
The initial random policy (t=0) is shown in the following chart:
Initial (t=0) random policy
The states denoted with ⊗ represent the wells, while the final positive one is represented by the capital letter ...
