activity
20232026
most citedFully Independent Communication in Multi-Agent Reinforcement Learning

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

collaborators

7 papers

cs.AR2026

Beyond Peak TOPS/W: A System-Level Perspective on Hybrid Digital, Analogue and Neuromorphic Computing

Eiman Kanjo, Varuna De Silva

The digital revolution, which progressively replaced analogue methods with digital circuits, has entered a new phase as AI expands across cloud infrastructure, mobile networks, wea…

cs.HC2026

ATRACT: A Trustworthy Robotic Autonomous system to support Casualty Triage

Tasweer Ahmad, Rafael Pina, Sandip Pradhan +6

At a time when drones are increasingly associated with hostile operations, we re-purpose them for humanitarian and life-saving applications. However, adapting search and rescue dro…

cs.LG20242 cited

Player Pressure Map -- A Novel Representation of Pressure in Soccer for Evaluating Player Performance in Different Game Contexts

Chaoyi Gu, Jiaming Na, Yisheng Pei +1

In soccer, contextual player performance metrics are invaluable to coaches. For example, the ability to perform under pressure during matches distinguishes the elite from the avera…

cs.LG20244 cited

Fully Independent Communication in Multi-Agent Reinforcement Learning

Rafael Pina, Varuna De Silva, Corentin Artaud +1

Multi-Agent Reinforcement Learning (MARL) comprises a broad area of research within the field of multi-agent systems. Several recent works have focused specifically on the study of…

cs.LG2023

Staged Reinforcement Learning for Complex Tasks through Decomposed Environments

Rafael Pina, Corentin Artaud, Xiaolan Liu +1

Reinforcement Learning (RL) is an area of growing interest in the field of artificial intelligence due to its many notable applications in diverse fields. Particularly within the c…

cs.LG2023

Learning Independently from Causality in Multi-Agent Environments

Rafael Pina, Varuna De Silva, Corentin Artaud

Multi-Agent Reinforcement Learning (MARL) comprises an area of growing interest in the field of machine learning. Despite notable advances, there are still problems that require in…