Spot why this agent never actually advances through the environment.
Codepython
state = env.reset()
done = False
while not done:
action = policy(state)
next_state, reward, done = env.step(action)
learn(state, action, reward, next_state)
# advance to the next state
state = state
What is the bug in this environment interaction loop?