Collaborative and Intelligent Multi-Agent Systems for Real-World Applications

Dear Colleagues,

Over the past few years, advances in artificial intelligence, distributed computing, and autonomous systems have accelerated the development of collaborative and intelligent multi-agent systems (MASs), making them capable of addressing increasingly complex real-world challenges, and enabling autonomous agents to work together, adapt dynamically, and even make decisions in uncertain and dynamic environments. With the growth of applications across various fields, there is growing research interest in designing innovative, scalable, explainable, and trustworthy MAS frameworks

In this Special Issue, we aim to present a research venue to publish highlights of cutting-edge theories, methodologies, and practical implementations in this fast-evolving research area.

Scope and Aims

This Special Issue aims to bring together researchers and practitioners to explore novel approaches, frameworks, and technologies that enhance the capabilities of MASs in solving real-world problems. Both original research articles and review papers are welcome.

Research areas may include (but are not limited to) the following:

Core MAS Research Directions

• Collaborative decision-making, coordination, and negotiation.
• Learning, adaptation, and self-organization in distributed systems.
• Scalable architectures, communication protocols, and interoperability.
• Multi-agent reinforcement learning and deep learning.
• Human–agent interaction and human-centered system design.
• Memory management and representation for agent reasoning.
• Integration of large generative models (LGMs) into MASs.
• Orchestration of AI pipelines and workflows in multi-agent contexts.
• Trust, privacy, and security in multi-agent collaboration.
• Explainability, transparency, and ethical issues.

Social Apps, Ubiquitous Computing, and Organizational Collaboration

• AI-driven governance structures for digital platforms and collaborative networks.
• Intelligent mechanisms for organizational alignment and resource coordination.
• Agent-based methods for social apps and ubiquitous computing, including ambient and urban intelligence, regulation of social behaviour, and collaborative tasks.
• Modelling features of individuals and groups in digital environments.
• Agent-based models of social behaviour, including group dynamics and micro–macro effects.
• Procedures and incentive mechanisms for coordinated action.
• Monitoring–recognition–intervention frameworks in social applications.
• Support for collaborative teams with flexible plan execution.
• Agreement formation and adherence in organizational and market domains.
• Robustness under uncertainty and incomplete information.
• Communication infrastructures for collaborative care involving human and artificial agents.
• Effects of transaction costs and organizational context on collaborative outcomes.

Social Analytics, Lifecycle Management, and Resilience

• Applying agents to next-generation social analytics systems in smarter societies.
• Understanding how organizational structures influence negotiation, task distribution, and execution in MASs.
• Supporting collaborative teams in scenarios such as collaborative research, resilient societies, and disaster resilience.
• Leveraging collaborative agent technology to analyse vast amounts of complex social data.
• Building models of individual behaviour (citizens, customers, patients) and group features.
• Incentive frameworks to encourage individuals to stay on track and achieve desired outcomes.
• Enabling flexible, goal-driven, and contextualized business process management, including intelligent execution, monitoring, and optimization.
• Investigating the role of learning and adaptivity in building organizational MASs.
• Addressing challenges in dealing with partially regulated markets, acknowledging that free markets rarely exist in practice.

Dr. Fernando Koch
Guest Editor

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. Applied System Innovation 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 1600 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.

• multi-agent systems
• distributed computing
• ubiquitous computing
• scalable computing
• human–agent interaction
• collaborative AI