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Many algorithms presented in this part are new to the second edition, including UCB, Expected Sarsa, and Double Learning. Part II extends these ideas to function approximation, with new sections on such topics as artificial neural networks and the Fourier basis, and offers expanded treatment of off-policy learning and policy-gradient methods. SARSA SARSA: Algorithm I Equivalent to Q-learning we initialise and maintain the table for Q with an entry for each valid state action pair (s;a). I Updating formula is similar to Q-learning with the exception that we can only take the actual next state into account. Q(s t;a t) = Q(s t;a t) + [r t + Q(s t+1;a t+1) Q(s t;a t)] where is the ...

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