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AHMA: An Adaptive Hierarchical Meta-Agent For Intelligent Congestion Control In IP Networks Using Machine Learning Cover

AHMA: An Adaptive Hierarchical Meta-Agent For Intelligent Congestion Control In IP Networks Using Machine Learning

Journal of Automation, Mobile Robotics and Intelligent Systems
Volume 20 (2026): Issue 2 (June 2026)
By:  and    
Open Access
|Jun 2026
Authors

Authors

Amit Kanungo

amitkanungo11@gmail.com

Department of Computer Science and Engineering, Medicaps University, Indore, India

Prashant Panse

prashant.panse@medicaps.ac.in

Department of Information Technology at Medicaps University in Indore, India
DOI: https://doi.org/10.14313/jamris-2026-026 | Journal eISSN: 2080-2145 | Journal ISSN: 1897-8649
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Language: English
Page range: 126 - 133
Submitted on: Jul 28, 2025
Accepted on: Sep 11, 2025
Published on: Jun 22, 2026
Published by: Łukasiewicz Research Network – Industrial Research Institute for Automation and Measurements PIAP
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
Keywords:
Adaptive Congestion Control,
Bayesian Transformer,
Congestion-Induced Losses,
IP Network Optimization,
Meta-Reinforcement Learning,
Packet loss classification
Related subjects:
Computer sciences,
Artificial intelligence,
Engineering,
Electrical engineering,
Control engineering, metrology and testing,
Mechanical engineering,
Fundamentals of mechanical engineering

© 2026 Amit Kanungo, Prashant Panse, published by Łukasiewicz Research Network – Industrial Research Institute for Automation and Measurements PIAP
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Volume 20 (2026): Issue 2 (June 2026)
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