7 citations · 7 across the 5 of their papers we have counts for
3 papers · 1 filter
Unsupervised Partner Design Enables Robust Ad-hoc Teamwork
Constantin Ruhdorfer, Matteo Bortoletto, Victor Oei +2
We introduce Unsupervised Partner Design (UPD), a population-free multi-agent reinforcement learning method for robust ad-hoc teamwork. UPD generates training partners on-the-fly a…
The Overcooked Generalisation Challenge: Evaluating Cooperation with Novel Partners in Unknown Environments Using Unsupervised Environment Design
Constantin Ruhdorfer, Matteo Bortoletto, Anna Penzkofer +1
We introduce the Overcooked Generalisation Challenge (OGC) - a new benchmark for evaluating reinforcement learning (RL) agents on their ability to cooperate with unknown partners i…
Int-HRL: Towards Intention-based Hierarchical Reinforcement Learning
Anna Penzkofer, Simon Schaefer, Florian Strohm +3
While deep reinforcement learning (RL) agents outperform humans on an increasing number of tasks, training them requires data equivalent to decades of human gameplay. Recent hierar…