Deep reinforcement learning is a machine learning technique that combines deep learning and reinforcement learning principles to enable agents to learn optimal behaviors through interactions with their environment. By utilizing neural networks, it allows the agent to process complex input data and make decisions that maximize cumulative rewards, adapting its strategy based on the feedback received from its actions.
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