notesum.ai
Published at October 23Leveraging Skills from Unlabeled Prior Data for Efficient Online Exploration
physics.comp-ph
cs.AI
Released Date: October 23, 2024
Authors: Max Wilcoxson1, Qiyang Li1, Kevin Frans1, Sergey Levine1
Aff.: 1UC Berkeley

| Parameter Name | Value |
|---|---|
| Batch size | 256 |
| Optimizer | Adam |
| Learning rate | |
| GRU Hidden Size | 256 |
| GRU Layers | 2 hidden layers |
| KL Coefficient ( | 0.1 |
| VAE Prior | state-conditioned isotropic Gaussian distribution over the latent |
| VAE Posterior | isotropic Gaussian distribution over the latent |
| Reconstruction Policy Decoder | isotropic Gaussian distribution over the action space |
| Latent Dimension | 8 |
| Trajectory Segment Length () | 4 |
| Image Encoder Latent Dim | 50 |