Control and Planning for Distributed Multi-Agent Systems

In recent years, distributed multi-agent systems (MAS) have gained significant attention across robotics, autonomous vehicles, sensor networks, and cyber-physical systems. The increasing complexity of real-world missions, ranging from cooperative transportation and environmental monitoring to smart grid coordination and swarm robotics, has made effective control and planning strategies essential for ensuring scalability, robustness, and adaptability in distributed settings.

Unlike centralized architectures, distributed multi-agent systems rely on local interactions, limited communication, and decentralized decision-making to achieve global objectives. This introduces several challenges, including handling communication constraints, time delays, uncertainties, dynamic topologies, and heterogeneous agent dynamics. Moreover, integrating control and planning under distributed frameworks requires new methodologies that can guarantee system-wide stability, convergence, and optimality.

Recent advances in control theory, optimization, game theory, learning-based methods, and artificial intelligence have opened promising directions for addressing these challenges. The proposed special issue aims to gather original contributions that present new theories, algorithms, and applications for control and planning in distributed multi-agent systems, emphasizing cross-disciplinary approaches that bridge classical control and modern intelligent systems.


This Research Topic invites original research articles, reviews, and perspectives that address recent developments and emerging trends in distributed multi-agent control and planning. Topics of interest include, but are not limited to:

- Distributed and Decentralized Control

- Multi-Agent Planning and Coordination

- Learning and Intelligence in Multi-Agent Systems

- Optimization and Game-Theoretic Approaches

- Applications (swarm robotics, autonomous vehicles, smart grids, environmental monitoring and industrial automation, etc)

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Editorial
• FAIR² Data
• Methods
• Mini Review
• Original Research
• Perspective
• Review

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Editorial
• FAIR² Data
• Methods
• Mini Review
• Original Research
• Perspective
• Review

Keywords: Distributed control, multi-agent systems, cooperative planning, decentralized optimization, consensus, formation control, reinforcement learning, game theory, adaptive control, swarm robotics, cyber-physical systems

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.