SYSTEMS AND METHODS FOR AUTONOMOUS NETWORK MANAGEMENT USING DEEP REINFORCEMENT LEARNING

Patent №

US 11,601,830

Granted

2023-03-07

Filed 2020

Owner

VERIZON PATENT AND LICENSING INC.

Lab

AI components

1

ml

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

17101749

A system described herein may provide a technique for analyzing metrics, parameters, attributes, and/or other information associated with networks or other devices or systems associated with high-dimensional data in order to determine potential configuration changes that may be made to such networks or other devices or systems in order to optimize and/or otherwise enhance the operation of such networks or other devices or systems. Multiple autoencoders associated with multiple dimensions may be used to calculate reconstruction errors or other features of data (e.g., metrics, parameters, etc.) that may be used to define operating or performance states of the network. Operating or performance states of network components may be mapped to quantum state objects (“QSOs”) for analysis using artificial intelligence and/or machine learning techniques or other suitable techniques.

Machine learningH04W 24/08G06N 3/045G06N 3/0455G06N 3/0464G06N 3/088G06N 3/092G06N 10/60H04L 41/0823+9 more

AI classification

Machine learning0.98
AI hardware0.36
Vision0.16
Planning0.08
Natural language0.00
Speech0.00
Evolutionary computation0.00
Knowledge representation0.00

Ownership

VERIZON PATENT AND LICENSING INC.

assignment · 544500623

Assignors

SOULHI, SAID, LARISH, BRYAN CHRISTOPHER

On an employer assignment, the assignors are typically the inventors.

From the same owner

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