Models, methods, algorithms

Igor Mayorov, Petr Skobelev. Multi-Agent Technology in Real-time Intelligent Resource Management Systems // Proceedings of the 4th International Conference on Intelligent Systems and Applications (INTELLI 2015), October 11 - 16, 2015, St. Julians, Malta. IARIA, P. 49-55.

The article describes the main principles of intelligent real-time resource management systems based on the use of multi-agent technology. Features of the new generation of systems are demonstrated that implement the full cycle of autonomous resource management, from reaction to real-world to monitoring deviations between the plan and the fact on the basis of the developed multi-agent platform. The article also presents several applications of scheduling systems in various areas, including cargo flow management for the International Space Station, workshop management in machine-building enterprises, railway traffic and cargo transportation management. Adaptability of multi-agent systems to external disruptive events is demonstrated. Finally, the similarities between multi-agent systems and non-equilibrium thermodynamics of Ilya Prigogine are described.

P.Skobelev. Multi-Agent Systems for Real Time Adaptive Resource Management. In Industrial Agents: Emerging Applications of Software Agents in Industry. Paulo Leitão, Stamatis Karnouskos (Ed.). Elsevier. 2015. pp. 207-230.

In this chapter, the approach for developing multi-agent solutions for solving real-tame scheduling problems will be presented, as well as examples of commercial applications that have been running in day-to-day operations for several years and have produced measurable and proven benefits.

Petr Skobelev, Igor Mayorov, Sergey Kozhevnikov, Alexander Tsarev, Elena Simonova. Measuring adaptability of "swarm intelligence" for resource scheduling and optimization in real time // Proceedings of the 7th International Conference on Agents and Artificial Intelligence (ICAART 2015), Lisbon, Portugal, 10-12 January, 2015, vol. 2. SCITEPRESS. P. 517-522.

In this paper modern methods of scheduling and resource optimization based on the holonic approach and principles of Swarm Intelligence are considered. The developed classes of holonic agents and method of adaptive real time scheduling where every agent is connected with individual satisfaction function by the set of criteria and bonus/penalty function are discussed. In this method the plan is considered as a un-stable equilibrium (consensus) of agents interests in dynamically self-organized network of demands and supply agents. The self-organization of plan demonstrates a swarm intelligence by spontaneous autocatalitical reactions and other not-linear behaviours. It is shown that multi-agent technology provides a generic framework for developing and researching various concepts of Swarm Intelligence for real time adaptive event-driving scheduling and optimization. The main result of research is the developed approach to evaluate the adaptability of Swarm Intelligence by measuring improve of value and transition time from one to another unstable state in case of disruptive events processing. Measuring adaptability helps to manage self-organized systems and provide better quality and efficiency of real time scheduling and optimization. This approach is under implementation in multi-agent platform for adaptive resource scheduling and optimization. The results of first experiments are presented and future steps of research are discussed.

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