Multi-agent Architecture for Federated Learning

  • Yuleisy Gonz´alez Perez Saint Petersburg Electrotechnical University, 5, building 3, st. Professora Popova, 197376, Saint Petersburg, Russia
  • Ivan Kholod Saint Petersburg Electrotechnical University, 5, building 3, st. Professora Popova, 197376, Saint Petersburg, Russia
Keywords: agent, architecture, federated learning, multi-agent systems

Abstract

The concept of federated learning has become widespread in working with data, mainly due to the fact that it allows training on data directly on the nodes where they are stored. As a result, no data transfer is required. After the training is completed on each node, only the trained model is transmitted to the central server for aggregation.
Multi-agent systems behave in a similar way, because agents allow you to train machine learning models on local devices, while preserving confidential information. The ability of agents to interact with each other makes it possible to generalize (aggregate) such models and reuse them.

This article presents the architecture of multi-agent systems for federated learning. It highlights the elements that make up the agent platform and the structure of the JADE platform. Describes the lifecycle of all agents used to perform a full training cycle in the MAC\_FL environment. The configurations of agent placement for each of the proposed architectures of multi-agent systems of federated learning are analyzed and described: centralized, decentralized and hierarchical.

Author Biographies

Yuleisy Gonz´alez Perez, Saint Petersburg Electrotechnical University, 5, building 3, st. Professora Popova, 197376, Saint Petersburg, Russia

Postgraduate of the Department of Computer Engineering of the Faculty of Computer Technologies and Informatics of Saint Petersburg Electrotechnical University,  yuleisy2688@gmail.com

Ivan Kholod, Saint Petersburg Electrotechnical University, 5, building 3, st. Professora Popova, 197376, Saint Petersburg, Russia

PhD, Associate Professor, Dean of the Faculty of Computer Technologies and Informatics of Saint Petersburg Electrotechnical University, iiholod@mail.ru

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Published
2022-03-28
How to Cite
Gonz´alez PerezY., & Kholod, I. (2022). Multi-agent Architecture for Federated Learning. Computer Tools in Education, (1), 30-45. https://doi.org/10.32603/2071-2340-2022-1-30-45
Section
Software Engineering