METHOD FOR JOINT OPTIMIZATION FEEDFORWARD ARTIFICIAL NEURAL NETWORKS WEIGHTS AND STRUCTURE IN DEEP MULTI-AGENT REINFORCEMENT LEARNING

METHOD FOR JOINT OPTIMIZATION FEEDFORWARD ARTIFICIAL NEURAL NETWORKS WEIGHTS AND STRUCTURE IN DEEP MULTI-AGENT REINFORCEMENT LEARNING

Increasing the intelligence of tasks solved using mobile cyber-physical systems (MCPS) requires the use of artificial neural networks (ANNs) and methods of multi-agent deep reinforcement learning (MDRL).

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Bibliographic Details
Main Author:	V. I. Petrenko
Format:	Article
Language:	Russian
Published:	North-Caucasus Federal University 2022-08-01
Series:	Современная наука и инновации
Subjects:	multi-agent deep reinforcement learning artificial neural networks mobile cyber-physical systems structure optimization
Online Access:	https://msi.elpub.ru/jour/article/view/309
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