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Application of neural networks in financial sphereThis article discusses the capabilities of Deep Reinforcement Learning algorithms in the field
Deep Reinforcement Learning Based Resource Allocation Method in Future Wireless Networks with Blockchain Assisted MEC Network reinforcement learning (RAMBAN) to address this issue because standard approaches are ineffective
The study of artificial neural networks on the example of a neural network for the game of TIC-TAC-toeThis paper discusses the main types of neural networks, their architecture and features. A task
Graph Neural Networks for Communication Networks: A SurveyCommunication networks are an important
infrastructure in contemporary society. In recent
AI development basen on neural network for Sea Battle gameThe paper provides an overview of the methods of training neural networks. The type of neural
Model predictive control for urban traffic flows reinforcement training obtained good parameters of the network model. © 2016 IEEE.
An empirical study of the naïve REINFORCE algorithm for predictive maintenance of REINFORCE against the policies of industry-grade implementations of three advanced algorithms – Deep Q-Network
Comparison of “Online-Q” and “Experience Replay” for Training a Neural Network in a Multi-Agent Environment game "mitos.is". When using a neural network in reinforced learning, difficulties arise with a high
Characterizing throughput and convergence time in dynamic multi-connectivity 5G deployments technologies (RATs) within a unified access network by allowing the user equipment (UE) to utilize them
Software-Technological Complex for Adaptive Control of a Production Cycle of Robotic Manufacturing
making intellectual system lays the idea of using neural network
controllers that solve the task
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