Deep reinforcement learning is a subfield of machine learning that combines reinforcement learning and deep learning.
Reinforcement learning considers a class of problem of computer agents having to evolve their actions from experiments and errors.
Deep reinforcement learning integrates deep learning into problem solving thus enabling agents to make decisions from reorganized input data without manual intervention.
Deep reinforcement learning algorithms are able to consider very large amounts of data and decide what actions to take to optimize a goal.
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