428 citations · 1.1k across the 13 of their papers we have counts for
3 papers · 1 filter
MAVEN: Multi-Agent Variational Exploration
Anuj Mahajan, Tabish Rashid, Mikayel Samvelyan +1
Centralised training with decentralised execution is an important setting for cooperative deep multi-agent reinforcement learning due to communication constraints during execution…
Exploration with Unreliable Intrinsic Reward in Multi-Agent Reinforcement Learning
Wendelin Böhmer, Tabish Rashid, Shimon Whiteson
This paper investigates the use of intrinsic reward to guide exploration in multi-agent reinforcement learning. We discuss the challenges in applying intrinsic reward to multiple c…
The StarCraft Multi-Agent Challenge
Mikayel Samvelyan, Tabish Rashid, Christian Schroeder de Witt +7
In the last few years, deep multi-agent reinforcement learning (RL) has become a highly active area of research. A particularly challenging class of problems in this area is partia…