activity
20202023
most citedA reinforcement learning control approach for underwater manipulation under position and torque constraints

11 citations · 19 across the 10 of their papers we have counts for

collaborators
Showing 2022Show all

5 papers · 1 filter

cs.MA2022★ 1 cited

Deep Reinforcement Learning for Multi-Agent Interaction

Ibrahim H. Ahmed, Cillian Brewitt, Ignacio Carlucho +14

The development of autonomous agents which can interact with other agents to accomplish a given task is a core area of research in artificial intelligence and machine learning. Tow…

cs.MA2022★ 1 cited

Few-Shot Teamwork

Elliot Fosong, Arrasy Rahman, Ignacio Carlucho +1

We propose the novel few-shot teamwork (FST) problem, where skilled agents trained in a team to complete one task are combined with skilled agents from different tasks, and togethe…

cs.MA2022

Cooperative Marine Operations via Ad Hoc Teams

Ignacio Carlucho, Arrasy Rahman, William Ard +3

While research in ad hoc teamwork has great potential for solving real-world robotic applications, most developments so far have been focusing on environments with simple dynamics.…

cs.LG2022★ 3 cited

Generating Teammates for Training Robust Ad Hoc Teamwork Agents via Best-Response Diversity

Arrasy Rahman, Elliot Fosong, Ignacio Carlucho +1

Ad hoc teamwork (AHT) is the challenge of designing a robust learner agent that effectively collaborates with unknown teammates without prior coordination mechanisms. Early approac…

cs.MA2022★ 3 cited

A Survey of Ad Hoc Teamwork Research

Reuth Mirsky, Ignacio Carlucho, Arrasy Rahman +5

Ad hoc teamwork is the research problem of designing agents that can collaborate with new teammates without prior coordination. This survey makes a two-fold contribution: First, it…