13 citations · 16 across the 3 of their papers we have counts for
5 papers
B-Pref: Benchmarking Preference-Based Reinforcement Learning
Kimin Lee, Laura Smith, Anca Dragan +1
Reinforcement learning (RL) requires access to a reward function that incentivizes the right behavior, but these are notoriously hard to specify for complex tasks. Preference-based…
Legged Robots that Keep on Learning: Fine-Tuning Locomotion Policies in the Real World
Laura Smith, J. Chase Kew, Xue Bin Peng +3
Legged robots are physically capable of traversing a wide range of challenging environments, but designing controllers that are sufficiently robust to handle this diversity has bee…
PEBBLE: Feedback-Efficient Interactive Reinforcement Learning via Relabeling Experience and Unsupervised Pre-training
Kimin Lee, Laura Smith, Pieter Abbeel
Conveying complex objectives to reinforcement learning (RL) agents can often be difficult, involving meticulous design of reward functions that are sufficiently informative yet eas…
AVID: Learning Multi-Stage Tasks via Pixel-Level Translation of Human Videos
Laura Smith, Nikita Dhawan, Marvin Zhang +2
Robotic reinforcement learning (RL) holds the promise of enabling robots to learn complex behaviors through experience. However, realizing this promise for long-horizon tasks in th…
Unsteady ballistic heat transport in infinite harmonic crystals
Vitaly A. Kuzkin
We study thermal processes in infinite harmonic crystals having a unit cell with arbitrary number of particles. Initially particles have zero displacements and random velocities, c…