5 citations · 8 across the 3 of their papers we have counts for
3 papers
Learning to Query Internet Text for Informing Reinforcement Learning Agents
Kolby Nottingham, Alekhya Pyla, Sameer Singh +1
Generalization to out of distribution tasks in reinforcement learning is a challenging problem. One successful approach improves generalization by conditioning policies on task or…
Guiding Global Placement With Reinforcement Learning
Robert Kirby, Kolby Nottingham, Rajarshi Roy +2
Recent advances in GPU accelerated global and detail placement have reduced the time to solution by an order of magnitude. This advancement allows us to leverage data driven optimi…
Modular Framework for Visuomotor Language Grounding
Kolby Nottingham, Litian Liang, Daeyun Shin +3
Natural language instruction following tasks serve as a valuable test-bed for grounded language and robotics research. However, data collection for these tasks is expensive and end…