66 citations · 167 across the 9 of their papers we have counts for
3 papers · 1 filter
A Generalist Agent
Scott Reed, Konrad Zolna, Emilio Parisotto +17
Inspired by progress in large-scale language modeling, we apply a similar approach towards building a single generalist agent beyond the realm of text outputs. The agent, which we…
Cross-Domain Perceptual Reward Functions
Ashley D. Edwards, Srijan Sood, Charles L. Isbell
In reinforcement learning, we often define goals by specifying rewards within desirable states. One problem with this approach is that we typically need to redefine the rewards eac…
Perceptual Reward Functions
Ashley Edwards, Charles Isbell, Atsuo Takanishi
Reinforcement learning problems are often described through rewards that indicate if an agent has completed some task. This specification can yield desirable behavior, however many…