Deep reinforcement learning is a type of machine learning that combines reinforcement learning with deep learning techniques. In this approach, an agent learns to make decisions by interacting with an environment and receiving feedback in the form of rewards or penalties, while using deep neural networks to process high-dimensional input data and represent complex policies.
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