Implementation of Multistep Quasimetric Estimator
Project description
Multistep Quasimetric Estimation - (wip)
Exploration and eventually practical implementation for the Multistep Quasimetric Estimation proposed by Zheng et al. of Berkeley
Citations
@misc{zheng2026multistepquasimetriclearningscalable,
title = {Multistep Quasimetric Learning for Scalable Goal-conditioned Reinforcement Learning},
author = {Bill Chunyuan Zheng and Vivek Myers and Benjamin Eysenbach and Sergey Levine},
year = {2026},
eprint = {2511.07730},
archivePrefix = {arXiv},
primaryClass = {cs.LG},
url = {https://arxiv.org/abs/2511.07730},
}
@misc{liu2023metricresidualnetworkssample,
title = {Metric Residual Networks for Sample Efficient Goal-Conditioned Reinforcement Learning},
author = {Bo Liu and Yihao Feng and Qiang Liu and Peter Stone},
year = {2023},
eprint = {2208.08133},
archivePrefix = {arXiv},
primaryClass = {cs.LG},
url = {https://arxiv.org/abs/2208.08133},
}
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
mqe-0.0.6.tar.gz
(5.5 kB
view details)
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
mqe-0.0.6-py3-none-any.whl
(4.6 kB
view details)
File details
Details for the file mqe-0.0.6.tar.gz.
File metadata
- Download URL: mqe-0.0.6.tar.gz
- Upload date:
- Size: 5.5 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: uv/0.8.17
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
8672c398de9f3fb846c003b7a291b6374997e08c655d2cf7b65f681a5cda8639
|
|
| MD5 |
25c1f7f4f99527967afd5597ff5a6f37
|
|
| BLAKE2b-256 |
7800c6816f869c1b5b55740bbb2a1bbc81e929bd796ce200208858fe85e53da3
|
File details
Details for the file mqe-0.0.6-py3-none-any.whl.
File metadata
- Download URL: mqe-0.0.6-py3-none-any.whl
- Upload date:
- Size: 4.6 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: uv/0.8.17
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
2e898c97e904435b1bdd9610f4d61a43107de27e6326ec899c496dc7dbbebe7a
|
|
| MD5 |
9cb52b3e79d58b3d39c39145f8e715f3
|
|
| BLAKE2b-256 |
a08095e556409718d6d3d7417cbf2c76ec65cfde7eb69b83d8b7dada20bd1e6a
|