Reinforcement Learning and Deep RL Python Theory and Projects - SARSA Implementation update

The video tutorial discusses the initialization and execution of a Q table in a learning algorithm. Initially, the old Q table is mentioned, and the process of reinitializing it with zeros is explained. The tutorial then demonstrates running the Q table and compares the results with previous runs, concluding that there is minimal difference in performance.

What was the initial state of the queue table before it was re-initialized?

What was the purpose of commenting out the print line for the queue table?

What was the percentage of the run after the changes were made to the queue table?

How many times was the Q table trained previously?

What difference was observed after re-initializing the queue table with zeros?