Artificial Intelligence, Data Science, Machine Learning, Reinforcement Learning, Programming.
rewards and lengths episode_rewards = [] episode_lengths = [] num_episodes = 1000 discount_factor = 0.99 # Train the agent using the REINFORCE algorithm for episode in range(num_episodes): # Reset the environment and get the initial state state = env.reset() episode_reward = 0 episode_length = 0 #