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1.5 Conclusion

Оглавление

Deep Reinforcement Learning is the fusion of reinforcement learning (RL) and deep learning. This field of research has been able to solve a wide range of dynamic decision-making operations that were traditionally out of control for a computer. In applications such as medical, automation, smart grids, banking, and plenty more, deep RL thus brings up many new applications. We give an overview of the deep reinforcement learning (RL) paradigm and learning algorithm choices. We begin with deep learning and reinforcement learning histories, as well as the implementation of the Markov method. Next, we summarize some popular applications in various fields and, eventually, we end up addressing some possible challenges in the future growth of DRL.

Artificial Intelligent Techniques for Wireless Communication and Networking

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