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Advancements in Practical Applications of Agents, Multi-Agent Systems and Digital...
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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 2025 | Viewed by 4490

Special Issue Editors

Prof. Dr. Philippe Mathieu

E-Mail Website
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
Special Issues, Collections and Topics in MDPI journals
Dr. Fernando De la Prieta Pintado

E-Mail Website
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
Dr. Alfonso González-Briones

E-Mail Website
Guest Editor
Department of Computer Science and Automation Control, University of Salamanca, 37007 Salamanca, Spain
Interests: smart cities; IoT; Industry 4.0; machine learning; artificial intelligence natural language processing; computational technologies; sentiment analysis
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
Dr. Fernando De la Prieta Pintado
Dr. Alfonso González-Briones
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Systems is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

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 (4 papers)

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34 pages, 1952 KiB  
Article
Using Large Language Models to Embed Relational Cues in the Dialogue of Collaborating Digital Twins
by Sana Salman and Deborah Richards
Systems 2025, 13(5), 353; https://doi.org/10.3390/systems13050353 - 6 May 2025
Viewed by 206
Abstract
Embodied Conversational Agents (ECAs) serve as digital twins (DTs), visually and behaviorally mirroring human counterparts in various roles, including healthcare coaching. While existing research primarily focuses on single-coach ECAs, our work explores the benefits of multi-coach virtual health sessions, where users engage with [...] Read more.
Embodied Conversational Agents (ECAs) serve as digital twins (DTs), visually and behaviorally mirroring human counterparts in various roles, including healthcare coaching. While existing research primarily focuses on single-coach ECAs, our work explores the benefits of multi-coach virtual health sessions, where users engage with specialized diet, physical, and cognitive coaches simultaneously. ECAs require verbal relational cues—such as empowerment, affirmation, and empathy—to foster user engagement and adherence. Our study integrates Generative AI to automate the embedding of these cues into coaching dialogues, ensuring the advice remains unchanged while enhancing delivery. We employ ChatGPT to generate empathetic and collaborative dialogues, comparing their effectiveness against manually crafted alternatives. Using three participant cohorts, we analyze user perception of the helpfulness of AI-generated versus human-generated relational cues. Additionally, we investigate whether AI-generated dialogues preserve the original advice’s semantics and whether human or automated validation better evaluates their lexical meaning. Our findings contribute to the automation of digital health coaching. Comparing ChatGPT- and human-generated dialogues for helpfulness, users rated human dialogues as more helpful, particularly for working alliance and affirmation cues, whereas AI-generated dialogues were equally effective for empowerment. By refining relational cues in AI-generated dialogues, this research paves the way for automated virtual health coaching solutions. Full article
(This article belongs to the Special Issue Advancements in Practical Applications of Agents, Multi-Agent Systems and Digital Twins)
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19 pages, 614 KiB  
Article
Empirical Analysis of Hierarchical Pathfinding in Lifelong Multi-Agent Pathfinding with Turns
by László Z. Varga
Systems 2025, 13(5), 331; https://doi.org/10.3390/systems13050331 - 1 May 2025
Viewed by 267
Abstract
Lifelong multi-agent pathfinding has two interrelated aspects: one is to find conflict-free paths for the agents, and the other is to resolve the conflicts among the agents in the best possible way. We focus on the first aspect by investigating three hierarchical pathfinding [...] Read more.
Lifelong multi-agent pathfinding has two interrelated aspects: one is to find conflict-free paths for the agents, and the other is to resolve the conflicts among the agents in the best possible way. We focus on the first aspect by investigating three hierarchical pathfinding approaches, while we apply the same conflict resolution method. We formally present the three pathfinding options: map reduction using fixed waypoints, map reduction using dynamic waypoints, and the classic grid region-based approach. We point out the problem of emerging conflicts in lifelong multi-agent pathfinding with turns. We describe how we evaluate the proposed solutions to example scenarios from the League of Robot Runners competition, and we formulate the goals of the empirical analysis. Based on the experimental results, we point out the need to find the sweet spot between response time and throughput. Full article
(This article belongs to the Special Issue Advancements in Practical Applications of Agents, Multi-Agent Systems and Digital Twins)
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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
Cited by 4 | Viewed by 2081
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
(This article belongs to the Special Issue Advancements in Practical Applications of Agents, Multi-Agent Systems and Digital Twins)
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Other

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15 pages, 1731 KiB  
Technical Note
FLAME-GPU for Traffic Systems: A Scalable Agent-Based Simulation Framework
by Maxim Smilovitskiy, Sedar Olmez, Paul Richmond, Robert Chisholm, Peter Heywood, Alvaro Cabrejas, Sven van den Berghe and Sachio Kobayashi
Systems 2025, 13(5), 376; https://doi.org/10.3390/systems13050376 - 14 May 2025
Viewed by 272
Abstract
Agent-based modelling (ABM) has revolutionised the simulation of complex systems, finding applications in diverse fields such as economic markets and traffic management. By modelling individuals as autonomous agents within a dynamic environment, ABM enables the exploration of system behaviours and the evaluation of [...] Read more.
Agent-based modelling (ABM) has revolutionised the simulation of complex systems, finding applications in diverse fields such as economic markets and traffic management. By modelling individuals as autonomous agents within a dynamic environment, ABM enables the exploration of system behaviours and the evaluation of interventions at various spatiotemporal resolutions. However, the computational intensity of ABM, particularly in large-scale simulations, remains a significant hurdle. This paper presents a novel approach to addressing these challenges through the development of a GPU-accelerated transport model, specifically applied to a road network. Utilising the FLAME-GPU framework, the proposed model demonstrates enhanced scalability and efficiency compared with traditional CPU-based simulations, such as Simulation of Urban MObility (SUMO). Through rigorous comparative analysis, this study highlights significant improvements in simulation speed and the capacity to manage larger vehicle populations. The research underscores the transformative potential of GPU acceleration in mitigating computational constraints within ABM, offering a practical framework for simulating transport systems with greater precision and depth. Extensive experimentation validates the model’s ability to realistically simulate the vehicle population of the Isle of Wight, achieving a balance between computational efficiency and the accurate representation of complex traffic dynamics. Full article
(This article belongs to the Special Issue Advancements in Practical Applications of Agents, Multi-Agent Systems and Digital Twins)
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