Guest Editors
Dr. André Filipe Sales Mendes
Email: andremendes@usal.es
Affiliation: Department of Computer Science and Automation, University of Salamanca, 37008 Salamanca, Spain
Homepage:
Research Interests: Computer Vision and Visual Perception
Multi-Agent Systems and Intelligent Decision-Making Architectures
Robotics and Human-Robot Interaction
Intelligent Systems for Real-Time Monitoring and Control
Dr. Héctor Sánchez San Blas
Email: hectorsanchezsanblas@usal.es
Affiliation: Department of Computer Science and Automation, University of Salamanca, 37008 Salamanca, Spain
Homepage:
Research Interests: Multi-Agent Systems and Intelligent Decision-Making Architectures
Computer Vision
Virtual Reality
Intelligent Systems for Real-Time Monitoring and Control
Dr. Diego Manuel Jiménez Bravo
Email: Dmjimenez@usal.es
Affiliation: Department of Computer Science and Automation, University of Salamanca, 37008 Salamanca, Spain
Homepage:
Research Interests: Multi-Agent Systems, Artificial Intelligence, IoT, Smart-homes, Energy Optimization
Summary
Multi-Agent Systems (MAS) represent a core paradigm in the development of intelligent, distributed solutions for complex and dynamic environments. Their ability to model autonomy, cooperation, and scalability makes them increasingly relevant across diverse sectors, from robotics and smart cities to education and logistics.
This Special Issue aims to showcase recent advances in Multi-Agent Systems, highlighting both foundational research and applied innovations. We seek contributions that address agent coordination, learning, decision-making, and integration with emerging technologies such as computer vision, robotics, and large language models. The issue will also explore how MAS contribute to real-world problem solving in domains like healthcare, cyber-physical systems, and intelligent transportation. By bringing together theoretical and experimental work, the issue will offer a comprehensive view of the current state and future directions of MAS research.
Suggested Themes
·Coordination and negotiation in dynamic MAS environments
·Learning and adaptation in multi-agent settings
·Human-agent and human-robot interaction
·Integration of MAS with large language models and vision systems
·Multi-agent architectures for smart environments and digital twins
·Applications of MAS in logistics, education, and healthcare
·Trust, ethics, and explainability in distributed intelligent systems
Keywords
multi-agent systems (MAS); agent coordination; reinforcement learning & adaptation; human-agent interaction; large language models (LLMs); computer vision integration; smart environments & digital twins; intelligent transportation & logistics
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