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Postby Lovebird » Fri Jan 11, 2019 9:17 pm

Enter Deep Learning! We combine Q Learning and Deep Learning, which yields Deep Q Networks. The idea is simple: we’ll replace the the Q Learning’s table with a neural network that tries to approximate Q Values. It is usually referred to as the approximator or the approximating function, and denoted as Q(s,a; θ), where θ represents the trainable weights of the network. http://qqoin.ru
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