Privacy-preserving resilient consensus for multi-agent systems in a general topology structure
Recent advances of consensus control have made it significant in multi-agent systems such
as in distributed machine learning, distributed multi-vehicle cooperative systems. However …
as in distributed machine learning, distributed multi-vehicle cooperative systems. However …
Resilient Mechanism Against Byzantine Failure for Distributed Deep Reinforcement Learning
Distributed deep reinforcement learning (DDRL) has been used in distributed systems to
better improve the adaptability. However, DDRL-based systems are also inevitably under …
better improve the adaptability. However, DDRL-based systems are also inevitably under …
Ad hoc teamwork in the presence of adversaries
Advances in ad hoc teamwork have the potential to create agents that collaborate robustly in
real-world applications. Agents deployed in the real world, however, are vulnerable to …
real-world applications. Agents deployed in the real world, however, are vulnerable to …
[PDF][PDF] Memory-Based Resilient Control Against Non-cooperation in Multi-agent Flocking
Inspired by natural flocking behaviors, researchers aim to develop a distributed control
approach for artificial agents to mimic these behaviors. The main challenge lies in …
approach for artificial agents to mimic these behaviors. The main challenge lies in …
Distributed Resilient Secondary Control for Microgrids with Attention-based Weights against High-density Misbehaving Agents
Y Li, L Wang - arxiv preprint arxiv:2409.11812, 2024 - arxiv.org
Microgrids (MGs) have been equipped with large-scale distributed energy sources (DESs),
and become more vulnerable due to the low inertia characteristic. In particular, high-density …
and become more vulnerable due to the low inertia characteristic. In particular, high-density …
Resilient Average Consensus in Presence of False Data Injection Attacks
B Li, Y Liu, Y Zhi, H Gao - 2023 42nd Chinese Control …, 2023 - ieeexplore.ieee.org
Average consensus is important for distributed multi-agent systems, with applications
ranging from network synchronization, load balancing for parallel processor, distributed …
ranging from network synchronization, load balancing for parallel processor, distributed …
An anti-consensus strategy based on continuous perturbation updates in opposite directions
In modern society, multi-agent consensus is applied in many applications such as
distributed machine learning, wireless sensor networks and so on. However, some agents …
distributed machine learning, wireless sensor networks and so on. However, some agents …