Q* Learning with FrozenLake.ipynb

For some runs, the value of the qtable does not change (outputs all zeros after Step 4.). I tried fixing the seed and still get different qtables at the end. Could you tell me why this would be the case?

Btw, awesome work on the reinforcement learning articles!

For some runs, the value of the qtable does not change (outputs all zeros after Step 4.). I tried fixing the seed and still get different qtables at the end. Could you tell me why this would be the case?

In step 4:

Remove:

step = 0
done = False

And add:
action = None
after
exp_exp_tradeoff = random.uniform(0, 1)

---> 30 qtable[state, action] = qtable[state, action] + learning_rate * (reward + gamma * np.max(qtable[new_state, :]) - qtable[state, action])
31
32

IndexError: arrays used as indices must be of integer (or boolean) type

Any idea why this is happening?

my code is exactly same but I am getting total 143 rewards in 10000(ten thousand) episode. very low accuracy

Hey there this code is obsolete check this instead: https://huggingface.co/learn/deep-rl-course/unit2/introduction