P. Skobelev. Towards Autonomous AI Systems for Resource Management: Applications in Industry and Lessons Learned // Y. Demazeau et al. (Eds.). Proceedings of the 16th International Conference on Practical Applications of Agents and Multiagent Systems (PAAMS 2018), Toledo, Spain, 20-22 June, 2018. – Advances in Practical Applications of Agents, Multi-Agent Systems, and Complexity. LNAI 10978. – Springer, Switzerland. – P. 12-25. DOI: https://doi.org/10.1007/978-3-319-94580-4_2
Complexity of modern resource management is analyzed and related with a number of decision makers, high variety of individual criteria, preferences and constraints, interdependency of all operations, etc. The overview of existing methods and tools of Enterprise Resource Planning is given and key requirements for resource management are specified. The concept of autonomous Artificial Intelligence (AI) systems for adaptive resource management based on multi-agent technology is discussed. Multi-agent model of virtual market and method for solving conflicts and finding consensus for adaptive resource management are presented. Functionality and architecture of autonomous AI systems for adaptive resource management and the approach for measuring adaptive intelligence and autonomy level in these systems are considered. Results of delivery of autonomous AI solutions for managing trucks and factories, mobile teams, supply chains, aerospace and railways are presented. Considerable increase of enterprise resources efficiency is shown. Lessons learned from industry applications are formulated and future developments of AI for solving extremely complex problems of adaptive resource management are outlined.
P.O. Skobelev, S.Yu. Borovik. On the way from INDUSTRY 4.0 to INDUSTRY 5.0: from digital manufacturing to digital society // International Scientific Journal INDUSTRY 4.0. – Scientific Technical Union of Mechanical Engineering, Bulgaria, Year II, is. 6(2017). – P. 307-311.
Nowadays the world is surviving the fourth industrial revolution named Industry 4.0, which combines physical world of real things with their “virtual twins”. The man with his intellect, creativity and will lies beyond this ideology. Now the image of a new paradigm of Industry 5.0 could be seen. It involves the penetration of Artificial Intelligence in man’s common life, their “cooperation” with the aim of enhancing the man capacity and the return of the man at the “Centre of the Universe”. The paper outlines modern technologies – from IoT up to emergent intelligence, being developed in organizations where authors work. The convergence of these technologies, according to our minds, will provide the transformation from Industry 4.0 to Industry 5.0.
Petr Skobelev, Damien Trentesaux. Disruptions Are the Norm: Cyber-Physical Multi-Agent Systems for Autonomous Real Time Resource Management // Borangiu, T., Trentesaux, D., Thomas, A., Leitao, P., Barata Oliveira, J.A. (Eds.): Proceedings of the 6th Workshop on Service Orientation in Holonic and Multi-Agent Manufacturing (SOHOMA16), October 6-7, 2016, Lisbon, Portugal. – «Service Orientation in Holonic and Multi-agent Manufacturing», series «Studies in Computational Intelligence», Vol. 694 – P. 287–294. – Springer International Publishing, Switzerland, 2016. DOI: 10.1007/978-3-319-51100-9.
This paper analyses the new requirements for real time resource management systems based on multi-agent technology. It shows the growing demand for developing autonomous systems which combines resource allocation, scheduling, optimization, communication with users and control in one cycle and can respond rapidly to unexpected events in real time. To solve the problem the cyber-physical multi-agent systems are considered. The paper also dwells on the new impact which such systems bring into design of modern systems on the way from smart Internet of things – to new organizations and ways of user motivation.
G. Rzevski, J. Knezevic, P. Skobelev, N. Borgest & O. Lakhin. Managing Aircraft Lifecycle Complexity // International Journal of Design & Nature and Ecodynamics. – 2016. – WIT Press, vol. 11(2016), is. 2. – pp. 77-87. DOI 10.2495/DNE-V11-N2-77-87.
A thorough analysis of data on aircraft lifecycle revealed inadequacy of current lifecycle management methods in the face of increased complexity of the Internet-based global market. A new method for managing lifecycle has been developed by authors and their teams using concepts and principles of the emerging complexity science with the aim of reducing lead times and costs. Centralised control has been replaced with distributed decision-making empowering all lifecycle stakeholders. The solution described in this paper is the first of its kind and it represents a genuine advance in knowledge, which leads to considerable reduction in design/production lead times and decrease in the lifecycle cost. The method has been validated in a variety of applications.
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.
I. Mayorov, P. Skobelev. Towards thermodynamics of real timescheduling // International Journal of Design & Nature and Ecodynamics. – WIT Press, vol. 10(2015), is. 3. – pp. 213-223. DOI 10.2495/DNE-V10-N3-213-223.
The modern problem of real-time resource management to increase enterprise efficiency is considered. A new look at the dynamic self-organizing processes based on multi-agent technologies in building and revising schedules by events in real time is suggested. Schedule is considered as a flexible network of operations of demand and resource agents. This schedule is formed during the interactions of basic agent classes that set and break the dynamic links between each other, depending on the events and changing situation in the real world.
A thermodynamic model of demand–resource network (DRN) dynamics is introduced. There is a similarity to Ilya Prigogine’s non-linear thermodynamics theory which allows us to explain the phenomenon of unstable equilibrium emergence, order and chaos, catastrophes, bifurcations and other non-linear events that are significant to the self-organizing processes control in multi-agent systems (MAS).
Managing Complexity is the first book that clearly defines the concept of Complexity, explains how Complexity can be measured and tuned. The thesis of the book is that complexity of the environment in which we work and live offers new opportunities and that the best strategy for surviving and prospering under conditions of complexity is to develop adaptability to perpetually changing conditions.An effective method for designing adaptability into business processes using multi-agent technology is presented and illustrated by several extensive examples, including adaptive, real-time scheduling of taxis, see-going tankers, road transport, supply chains, railway trains, production processes and swarms of small space satellites. Additional case studies include adaptive servicing of the International Space Station; adaptive processing of design changes of large structures such as wings of the largest airliner in the world; dynamic data mining, knowledge discovery and distributed semantic processing.