Question: Write a Q-learning implementation that learns the value of each state-action pair for a game of tic-tac-toe by repeatedly playing against human opponents. No function

Write a Q-learning implementation that learns the value of each state-action pair for a game of tic-tac-toe by repeatedly playing against human opponents. No function approximators are used and therefore the entire table of state-action pairs is learned using Equation 10.4. Assume that you can initialize each Q-value to 0 in the table.

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