The Q-learning approximation algorithm starts with an initial parameter estimate of 0. As the tabular Q-learning, upon observing a data tuple (s, c, R (s, c), s'), the target value y for the Q-value of (s, c) is defined as the sampled version of the Bellman operator, y= R(s,c) + ym )+7max Q (s', c', 0).

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