1.5k citations · 3.5k across the 13 of their papers we have counts for
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Exploration by Random Network Distillation
Yuri Burda, Harrison Edwards, Amos Storkey +1
We introduce an exploration bonus for deep reinforcement learning methods that is easy to implement and adds minimal overhead to the computation performed. The bonus is the error o…
How to train your MAML
Antreas Antoniou, Harrison Edwards, Amos Storkey
The field of few-shot learning has recently seen substantial advancements. Most of these advancements came from casting few-shot learning as a meta-learning problem. Model Agnostic…
Large-Scale Study of Curiosity-Driven Learning
Yuri Burda, Harri Edwards, Deepak Pathak +3
Reinforcement learning algorithms rely on carefully engineering environment rewards that are extrinsic to the agent. However, annotating each environment with hand-designed, dense…
Learning Policy Representations in Multiagent Systems
Aditya Grover, Maruan Al-Shedivat, Jayesh K. Gupta +2
Modeling agent behavior is central to understanding the emergence of complex phenomena in multiagent systems. Prior work in agent modeling has largely been task-specific and driven…
Variational Option Discovery Algorithms
Joshua Achiam, Harrison Edwards, Dario Amodei +1
We explore methods for option discovery based on variational inference and make two algorithmic contributions. First: we highlight a tight connection between variational option dis…