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Explore deep Q-networks in this comprehensive 41-minute lecture by Pascal Poupart. Delve into key concepts including approximation, optimization, Q-learning, gradient Q-learning, and experience replay. Learn about divergence issues and their solutions, gradient descent techniques, and the implementation of target networks. Discover the architecture and algorithm behind deep Q-networks, and examine their performance results in various applications.
