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Found 7 papers, 1 papers with code
Distributed Autonomous Swarm Formation for Dynamic Network Bridging
Effective operation and seamless cooperation of robotic systems are a fundamental component of next-generation technologies and applications.
Multi-Agent Reinforcement Learning with Control-Theoretic Safety Guarantees for Dynamic Network Bridging
Addressing complex cooperative tasks in safety-critical environments poses significant challenges for Multi-Agent Systems, especially under conditions of partial observability.
Collaborative Information Dissemination with Graph-based Multi-Agent Reinforcement Learning
Efficient information dissemination is crucial for supporting critical operations across domains like disaster response, autonomous vehicles, and sensor networks.
Learning to Sail Dynamic Networks: The MARLIN Reinforcement Learning Framework for Congestion Control in Tactical Environments
Conventional Congestion Control (CC) algorithms, such as TCP Cubic, struggle in tactical environments as they misinterpret packet loss and fluctuating network performance as congestion symptoms.
HeteroEdge: Addressing Asymmetry in Heterogeneous Collaborative Autonomous Systems
Finally, we propose and optimize a novel parameter split-ratio, which indicates the proportion of the data required to be offloaded to another device while considering the networking bandwidth, busy factor, memory (CPU, GPU, RAM), and power constraints of the devices in the testbed.
Enhancing object detection robustness: A synthetic and natural perturbation approach
Robustness against real-world distribution shifts is crucial for the successful deployment of object detection models in practical applications.
MARLIN: Soft Actor-Critic based Reinforcement Learning for Congestion Control in Real Networks
Fast and efficient transport protocols are the foundation of an increasingly distributed world.
