Advancements in Practical Applications of Agents, Multi-Agent Systems and Digital Twins

A special issue of Systems (ISSN 2079-8954). This special issue belongs to the section "Systems Engineering".

Deadline for manuscript submissions: 31 December 2024 | Viewed by 1397

Special Issue Editors


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Guest Editor
Department of Computer Science, Lille University, Cité Scientifique, 59650 Villeneuve-d’Ascq, France
Interests: artificial intelligence; multi-agent systems; individual based simulation; agent based computational economics; game theory
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Guest Editor
1. BISITE Research Group, University of Salamanca, 37007 Salamanca, Spain
2. Air Institute, IoT Digital Innovation Hub, 37188 Salamanca, Spain
3. Department of Electronics, Information and Communication, Faculty of Engineering, Osaka Institute of Technology, Osaka 535-8585, Japan
Interests: artificial intelligence; smart cities; smart grids
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
BISITE Research Group, University of Salamanca, Edificio Multiusos I+D+I, 37007 Salamanca, Spain
Interests: artificial intelligence; multi-agent systems; cloud computing and distributed systems; technology-enhanced learning
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Digital Twins are an innovative virtual representation of physical systems, providing a platform for the advanced simulation, comprehensive analysis and reliable prediction of the behavior of real-world systems. Given their cross-cutting nature, Digital Twins find applicability in a wide range of industries, including, but not limited to, manufacturing, healthcare, logistics and smart city domains. Digital twin modeling and simulation involves the use of advanced modeling techniques to build highly accurate digital representations that faithfully reflect both the dynamic and static characteristics of physical systems. Analysis and optimization are presented as a central focus in this field, using data from sensors and other IoT devices to enhance system performance and anticipate potential failures.

The application of multiagent systems in digital twins emerges as a powerful tool in this scenario, where collaboration and interaction between autonomous agents contribute significantly to the effective management and control of digital twins. This collaboration results in the superior adaptability and scalability of the simulated system. Interoperability and standards are equally vital, as effective communication between digital twins and pre-existing systems is essential to ensure integration and information flow. No less important is the dimension of cybersecurity in digital twins, where strategies are proposed to safeguard data integrity and ensure functionality in the face of growing security threats in cyberspace. It also emphasizes the importance of sharing use cases and practical applications that illustrate the successful implementation of digital twins in different contexts, highlighting both their benefits and challenges.

Digital Twins are at the forefront of the simulation and analysis of complex systems, where multi-agent agents and systems emerge as critical elements for the creation of interactive and reactive simulations of the real world. Synergistic collaboration between these agents leads to highly accurate simulations, resulting in well-informed, data-driven decisions.

This Special Issue invites researchers to submit original quality studies regarding the domain of digital twins. Submitted manuscripts should explore the enhancement of digital twins through multi-agent systems, highlighting how the latter bring robustness, efficiency, and adaptability to simulations. We encourage the submission of cutting-edge methodologies that advance the field of digital twins, as well as analyses that reflect on current and future trends in the field.

Prof. Dr. Philippe Mathieu
Prof. Dr. Juan M. Corchado
Dr. Fernando De la Prieta Pintado
Dr. Alfonso González-Briones
Guest Editors

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Keywords

  • digital twins
  • simulating digital twins
  • simulation, modelling and analysis techniques
  • reasoning in digital twins
  • mathematical modeling
  • distributed problem solving
  • agent-based simulation
  • multi-agent systems (MAS)
  • IoT and MAS
  • CPS and MAS
  • IoT, smart cities, Industry 4.0
  • cybersecurity and digital twins
  • ambient intelligence

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Published Papers (1 paper)

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Research

18 pages, 7186 KiB  
Article
Airside Optimization Framework Covering Multiple Operations in Civil Airport Systems with a Variety of Aircraft: A Simulation-Based Digital Twin
by Ahmad Attar, Mahdi Babaee, Sadigh Raissi and Majid Nojavan
Systems 2024, 12(10), 394; https://doi.org/10.3390/systems12100394 - 26 Sep 2024
Viewed by 621
Abstract
The airside is a principal subsystem in the intricate airport systems. This study focuses on introducing a digital twin framework for analyzing the delays and capacity of airports. This framework encompasses a diverse array of authentic features pertaining to a civil airport for [...] Read more.
The airside is a principal subsystem in the intricate airport systems. This study focuses on introducing a digital twin framework for analyzing the delays and capacity of airports. This framework encompasses a diverse array of authentic features pertaining to a civil airport for a mixture of both landing and departing flights. Being a decision support for the management of international airports, all sizes and weight categories of aircraft are considered permissible, each with their own unique service time and speed requirements in accordance with the global aviation regulations. The proposed discrete event simulation digital twin provides a real-time demonstration of the system performance with the possibility of predicting the future outcomes of managerial decisions. Additionally, this twin is equipped with an advanced and realistic 3D visualization that facilitates a more comprehensive understanding of the ongoing operations. To assess its efficiency in practice, the framework was implemented at an international airport. The statistical tests revealed the superior similarity between the proposed twin and the real system. Using this twin, we further optimized the studied system by analyzing its projected future performance under a set of scenarios. This resulted in a nearly 30% upgrade in the capacity of this airport while decreasing the expected delays by over 18% annually. Full article
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