297 citations · 1.5k across the 27 of their papers we have counts for
4 papers · 1 filter
Stabilizing Transformers for Reinforcement Learning
Emilio Parisotto, H. Francis Song, Jack W. Rae +10
Owing to their ability to both effectively integrate information over long time horizons and scale to massive amounts of data, self-attention architectures have recently shown brea…
Efficient Exploration via State Marginal Matching
Lisa Lee, Benjamin Eysenbach, Emilio Parisotto +3
Exploration is critical to a reinforcement learning agent's performance in its given environment. Prior exploration methods are often based on using heuristic auxiliary predictions…
Concurrent Meta Reinforcement Learning
Emilio Parisotto, Soham Ghosh, Sai Bhargav Yalamanchi +3
State-of-the-art meta reinforcement learning algorithms typically assume the setting of a single agent interacting with its environment in a sequential manner. A negative side-effe…
The Hanabi Challenge: A New Frontier for AI Research
Nolan Bard, Jakob N. Foerster, Sarath Chandar +12
From the early days of computing, games have been important testbeds for studying how well machines can do sophisticated decision making. In recent years, machine learning has made…