Development of Artificial Intelligence by Ensembles of Virtual Agents with Mobile Interaction
Automation, Control and Intelligent Systems
Volume 8, Issue 1, February 2020, Pages: 1-8
Received: Jan. 4, 2020; Accepted: Jan. 10, 2020; Published: Apr. 13, 2020
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Evgeniy Bryndin, Research Department, Research Center "Natural Informatics", Novosibirsk, Russia
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Process automation, cloud technology, machine learning, big data analytics, and the Internet of Things have changed the fundamental pillars of the high-tech industry, according to Deloitte's report of Future of Working in the World of Technology. The Harvard Business Review Analytic Services study to marks the race for technology across all industries. The digital transformation of the high-tech industry and social sphere currently requires rapid reactions and flexible mobility. Smart collaboration agents are beginning to demonstrate the ability to work together effectively. Smart agent ensembles use information from technology platforms such as the European Technology Platform Future Manufacturing Technologies and analytics platforms such as Visiology, which quickly and efficiently addresses the challenges of collecting, analyzing and visualizing large amounts of data. Fast, efficient data collection and analysis of large amounts of data, flexible operational mobility of data updates, and synergistic open collaboration of smart agents with information platforms and analytical systems will help accelerate the digital transformation of the high-tech industry and social sphere by teaching new skills. Learning new skills can be done in a virtual space and then developed in a specific environment. The accumulation of professional experience in virtual space contributes to the development of artificial intelligence.
Virtual Ensemble of Agents, Technological Platforms, Analytical Systems, Development of Artificial Intelligence
To cite this article
Evgeniy Bryndin, Development of Artificial Intelligence by Ensembles of Virtual Agents with Mobile Interaction, Automation, Control and Intelligent Systems. Vol. 8, No. 1, 2020, pp. 1-8. doi: 10.11648/j.acis.20200801.11
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