301 citations · 439 across the 27 of their papers we have counts for
3 papers · 1 filter
Replay-Guided Adversarial Environment Design
Minqi Jiang, Michael Dennis, Jack Parker-Holder +3
Deep reinforcement learning (RL) agents may successfully generalize to new settings if trained on an appropriately diverse set of environment and task configurations. Unsupervised…
MiniHack the Planet: A Sandbox for Open-Ended Reinforcement Learning Research
Mikayel Samvelyan, Robert Kirk, Vitaly Kurin +7
Progress in deep reinforcement learning (RL) is heavily driven by the availability of challenging benchmarks used for training agents. However, benchmarks that are widely adopted b…
Grid-to-Graph: Flexible Spatial Relational Inductive Biases for Reinforcement Learning
Zhengyao Jiang, Pasquale Minervini, Minqi Jiang +1
Although reinforcement learning has been successfully applied in many domains in recent years, we still lack agents that can systematically generalize. While relational inductive b…