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

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 250 words) can be sent to the Editorial Office for assessment.

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.