Advances in Distributed Intelligence and Multi-Agent Systems

Dear Colleagues,

Distributed intelligence and multi-agent systems have emerged as fundamental paradigms in artificial intelligence, enabling autonomous decision-making, efficient coordination, and collaborative problem-solving in dynamic and complex environments. The proliferation of interconnected intelligent agents has transformed various domains, including robotics, smart cities, autonomous transportation, industrial automation, and edge computing. As these systems continue to evolve, challenges related to scalability, robustness, security, and real-time adaptation remain critical areas of research. Addressing these challenges is essential for the development of intelligent, autonomous, and cooperative systems capable of performing tasks efficiently in decentralized settings.

This Special Issue aims to explore recent advancements in distributed intelligence and multi-agent systems, emphasizing theoretical foundations, algorithmic developments, and practical applications. By bridging interdisciplinary perspectives, we seek to highlight novel methodologies that enhance coordination, decision-making, and learning in multi-agent settings.

We extend an invitation for the submission of original research articles and comprehensive reviews covering, but are not necessarily limited to, the following topics:

1. Theoretical Advances in Multi-Agent Systems

Distributed optimization and game theory for multi-agent interactions;

Learning-based coordination and decentralized decision-making;

Emergent behaviors and swarm intelligence.

2. Distributed Intelligence in Dynamic Environments

Reinforcement learning for decentralized control;

Adaptive and self-organizing multi-agent architectures;

Trust, privacy, and security in distributed AI systems.

3. Applications of Multi-Agent Systems

Autonomous vehicles and traffic management;

Smart grids and energy-efficient distributed intelligence;

Robotics, Human–Robot collaboration, and swarm robotics;

Edge AI and federated learning in multi-agent contexts.

4. Scalability and Robustness in Distributed Systems

Fault tolerance and resilience in decentralized AI;

Efficient communication and resource allocation strategies;

Scalability challenges in large-scale multi-agent deployments.

We welcome contributions that address these themes through theoretical analyses, experimental studies, and real-world applications.

We look forward to receiving your valuable contributions to this Special Issue.

Dr. Meng Li
Dr. Shunchao Wang
Dr. Haoxuan Dong
Guest Editors

Manuscript Submission Information

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