activity
20232025
most citedMARLIN: Soft Actor-Critic based Reinforcement Learning for Congestion Control in Real Networks

7 citations · 11 across the 6 of their papers we have counts for

collaborators

7 papers

cs.CL2025

Natural Language Interaction with Databases on Edge Devices in the Internet of Battlefield Things

Christopher D. Molek, Roberto Fronteddu, K. Brent Venable +1

The expansion of the Internet of Things (IoT) in the battlefield, Internet of Battlefield Things (IoBT), gives rise to new opportunities for enhancing situational awareness. To inc…

cs.MA2024

Distributed Autonomous Swarm Formation for Dynamic Network Bridging

Raffaele Galliera, Thies Möhlenhof, Alessandro Amato +3

Effective operation and seamless cooperation of robotic systems are a fundamental component of next-generation technologies and applications. In contexts such as disaster response,…

cs.MA2024

Safety-Aware Multi-Agent Learning for Dynamic Network Bridging

Raffaele Galliera, Konstantinos Mitsopoulos, Niranjan Suri +1

Addressing complex cooperative tasks in safety-critical environments poses significant challenges for multi-agent systems, especially under conditions of partial observability. We…

cs.LG2023★ 1 cited

Collaborative Information Dissemination with Graph-based Multi-Agent Reinforcement Learning

Raffaele Galliera, Kristen Brent Venable, Matteo Bassani +1

Efficient information dissemination is crucial for supporting critical operations across domains like disaster response, autonomous vehicles, and sensor networks. This paper introd…

cs.DC2023

HeteroEdge: Addressing Asymmetry in Heterogeneous Collaborative Autonomous Systems

Mohammad Saeid Anwar, Emon Dey, Maloy Kumar Devnath +8

Gathering knowledge about surroundings and generating situational awareness for IoT devices is of utmost importance for systems developed for smart urban and uncontested environmen…

cs.CV2023★ 3 cited

Enhancing object detection robustness: A synthetic and natural perturbation approach

Nilantha Premakumara, Brian Jalaian, Niranjan Suri +1

Robustness against real-world distribution shifts is crucial for the successful deployment of object detection models in practical applications. In this paper, we address the probl…

cs.LG2023★ 7 cited

MARLIN: Soft Actor-Critic based Reinforcement Learning for Congestion Control in Real Networks

Raffaele Galliera, Alessandro Morelli, Roberto Fronteddu +1

Fast and efficient transport protocols are the foundation of an increasingly distributed world. The burden of continuously delivering improved communication performance to support…