problem: in order to speed up data generation, we cannot run the task faster than in real time.
Delayed Rewards
Most real systems have interruptions in the state’s sensation, the actuators, or the feedback on the reward. For instance, delays in the effects of a braking system, or delays between a recommendation system’s choices and consequent user behaviors. There are a number of possible methods to deal with this, including memory-based agents that leverage a memory recovery system to allocate credit to distant past events that are helpful in forecasting [1, 15].
1.5 Conclusion
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.
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1 * Corresponding author: [email protected]
2
Impact of AI in 5G Wireless Technologies and Communication Systems
A. Sivasundari* and K. Ananthajothi†
Department of Computer Science and Engineering, Misrimal Navajee Munoth Jain Engineering College, Chennai, India
Abstract
4G networks (with Internet Protocol or IP, telecommunications and reaction-based connectivity) have managed the network architecture. They have evolved and are now accessible in a multitude of ways, including advanced learning and deep learning. 5G is flexible and responsive and will establish the need for integrated real time decision-making. As the rollout has begun across the globe, recent technical and architectural developments in 5G networks have proved their value. In various fields of classification, recognition and automation, AI has already proved its efficacy with greater precision. The integration of artificial intelligence with internet-connected computers and superfast 5G wireless networks opens up possibilities around the globe and even in outer space. In this section, we offer an in-depth overview of the Artificial Intelligence implementation of 5G wireless communication systems. The focus of this research is in this context, to examine the application of AI and 5G in warehouse building and to discuss the role and difficulties faced, and to highlight suggestions for future studies on integrating Advanced AI in 5G wireless communications.
Keywords:
