Distributed Topology Reconfiguration for Open Multiagent Systems via Algebraic Connectivity and Kirchhoff Index.

Area of Science:

• Robotics and Control Systems
• Network Science
• Distributed Systems

Background:

• Open multiagent systems (MASs) face challenges with dynamic agent participation.
• Existing topology control methods often rely on myopic greedy strategies, leading to suboptimal network structures.
• Decentralized control in dynamic networks requires robust topology management.

Purpose of the Study:

• To propose a distributed topology reconfiguration protocol for open MASs with dynamic agent entries and exits.
• To overcome limitations of traditional greedy approaches by incorporating global network metrics.
• To enable decentralized decision-making for network maintenance and adaptation.

Main Methods:

• Introduced the Kirchhoff index as a global metric alongside algebraic connectivity.
• Formulated a unified network improvement index (UNII) balancing local and global network properties.
• Developed distributed spectral estimation algorithms for decentralized UNII computation and protocol execution.

Main Results:

• The UNII protocol consistently creates topologies with superior algebraic connectivity and robustness.
• Achieved better performance compared to benchmark strategies in dynamic network scenarios.
• Demonstrated significant reduction in steady-state mean squared error for cooperative control tasks.

Conclusions:

• The proposed UNII protocol offers an effective and scalable solution for dynamic open-topology MASs.
• The method enhances network robustness and control performance in the face of agent mobility.
• Decentralized spectral methods provide a powerful tool for adaptive network management.