Submission Deadline: 31 March 2026 View: 615 Submit to Special Issue
Prof. Md Abdus Samad Kamal
Email: maskamal@gunma-u.ac.jp
Affiliation: Cluster of Electronics and Mechanical Engineering, Graduate School of Science and Technology, Gunma University, Kiryu 376-8515, Japan
Research Interests: intelligent transportation systems, swarm robotics, multi-agent systems, autonomous driving

Assoc. Prof. Mahmud Iwan Solihin
Email: mahmudis@ucsiuniversity.edu.my
Affiliation: Mechanical and Mechatronics Engineering, UCSI University, Cheras 56000 Kuala Lumpur, Malaysia
Research Interests: intelligent systems, robotic and automation, meta-heuristic optimization, artificial intelligence

This Special Issue aims to explore cutting-edge research in cooperative intelligence and distributed control utilizing a multiagent framework. As multiagent systems become increasingly central to fields such as intelligent transportation, drones, robotics, sensor networks, and smart infrastructure, there is a growing need for innovative frameworks enabling agents to coordinate, collaborate, and adapt in dynamic environments. Specifically, as autonomous agents increasingly interact in complex, dynamic environments, there is a critical need for scalable, decentralized, and intelligent coordination strategies for realistic employment in real-world systems. The special issue will be promoted as a platform for novel theoretical frameworks, algorithmic innovations, and real-world applications.
We welcome high-quality original research and review papers on topics including, but not limited to:
· Consensus of multiagent system
· Hierarchical, distributed, and decentralized control methods
· Cooperative decision-making and consensus algorithms
· Multiagent learning and adaptation
· Traffic and transportation systems
· Swarm robotics and autonomous vehicle coordination
· Smart infrastructure and energy networks
By bringing together interdisciplinary perspectives, this issue will promote the development of robust, efficient, and scalable multiagent systems across domains.


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