for in range(num_episodes)state env reset(episode_reward while trueaction env action_space sample(state rewarddone_ env step(actionepisode_reward +reward state state if donerewards append(episode_reward)break nextadd the ability for the agent to trade off between exploration and exploitation right before your main game loop (which starts with for )create the -value table/ataribot/bot_ _q_table py np zeros((env observation_space nenv action_space )for in range(num_episodes)thenrewrite the for loop to expose the episode number/ataribot/bot_ _q_table py