Abstract
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.
Highlights
In classical artificial intelligence theory, the solution to any problem is to create some one intelligent system, called an agent, which, having at its disposal all the necessary knowledge, abilities and computational resources, is able to solve some global problem
Multi-agent systems are the direction of artificial intelligence that uses ensembles consisting of multiple interacting agents to solve a complex problem or problem
The process of decomposition of the global problem and the inverse process of composition of the found solutions takes place under the control of some single "center." At the same time, the creative ensemble is designed strictly from top to bottom, based on the roles defined for the agents and the results of dividing the global task into subtasks
Summary
In classical artificial intelligence theory, the solution to any problem is to create some one intelligent system, called an agent, which, having at its disposal all the necessary knowledge, abilities and computational resources, is able to solve some global problem. Multi-agent systems are the direction of artificial intelligence that uses ensembles consisting of multiple interacting agents to solve a complex problem or problem. In multi-agent systems, the entire spectrum of tasks under certain rules is distributed among all agents, each of whom is considered a member of the ensemble. To organize the task distribution process, a multi-agent system creates either a distributed problem resolution ensemble or decentralized artificial intelligence. The multi-agent system is designed strictly from top to bottom, based on the roles defined for the agents and the results of dividing the global task into subtasks. In the case of decentralized artificial intelligence, job distribution occurs during agent interaction. This results in resonance, synergistic effects in multi-agent systems
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