THE MANAGEMENT PROCESS OF ORGANIZATIONS ADOPTING MULTI-AGENT SYSTEMS THAT SUSTAIN THE ACCELERATION OF DISTRIBUTED NEURAL NETWORKS AT SCALE

The paper intends to investigate the management process for adopting multi-agent systems and their impact on a data-driven organization. While enabling distributed artificial intelligence to process data, today's organizations gain additional knowledge over insights provided by artificial neural networks present through multi-agent systems. Distributed neural networks revolutionize the decision-making, prediction ability, and real-time reactivity systems of the mobility and industrial landscape of present times. Contributions and conclusions emerge from leveraging impact and observations from various use cases, and critical aspects regarding the management process are revealed and highlighted. The purpose is to uncover technological, legal, ethical, and social aspects and stimulate the adoption of distributed artificial intelligence through the joint development of machine learning through multi-agent systems.

• Publication year

  2020

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• Identifiers
  DOI 10.24818/imc/2020/01.11
• External record

  Open on Semantic Scholar

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  Semantic Scholar

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