125 citations · 233 across the 37 of their papers we have counts for
19 papers · 1 filter
SMAClite: A Lightweight Environment for Multi-Agent Reinforcement Learning
Adam Michalski, Filippos Christianos, Stefano V. Albrecht
There is a lack of standard benchmarks for Multi-Agent Reinforcement Learning (MARL) algorithms. The Starcraft Multi-Agent Challenge (SMAC) has been widely used in MARL research, b…
Conditional Mutual Information for Disentangled Representations in Reinforcement Learning
Mhairi Dunion, Trevor McInroe, Kevin Sebastian Luck +2
Reinforcement Learning (RL) environments can produce training data with spurious correlations between features due to the amount of training data or its limited feature coverage. T…
Using Offline Data to Speed Up Reinforcement Learning in Procedurally Generated Environments
Alain Andres, Lukas Schäfer, Stefano V. Albrecht +1
One of the key challenges of Reinforcement Learning (RL) is the ability of agents to generalise their learned policy to unseen settings. Moreover, training RL agents requires large…
Revisiting the Gumbel-Softmax in MADDPG
Callum Rhys Tilbury, Filippos Christianos, Stefano V. Albrecht
MADDPG is an algorithm in multi-agent reinforcement learning (MARL) that extends the popular single-agent method, DDPG, to multi-agent scenarios. Importantly, DDPG is an algorithm…
Scalable Multi-Agent Reinforcement Learning for Warehouse Logistics with Robotic and Human Co-Workers
Aleksandar Krnjaic, Raul D. Steleac, Jonathan D. Thomas +8
We consider a warehouse in which dozens of mobile robots and human pickers work together to collect and deliver items within the warehouse. The fundamental problem we tackle, calle…
Planning with Occluded Traffic Agents using Bi-Level Variational Occlusion Models
Filippos Christianos, Peter Karkus, Boris Ivanovic +2
Reasoning with occluded traffic agents is a significant open challenge for planning for autonomous vehicles. Recent deep learning models have shown impressive results for predictin…