deep_ope
RL benchmarks
Provides benchmarking policies and datasets for offline reinforcement learning
85 stars
8 watching
9 forks
Language: Jupyter Notebook
last commit: over 1 year ago
Linked from 1 awesome list
hanjuku-kaso/awesome-offline-rlRelated projects:
| Repository | Description | Stars |
|---|---|---|
 rll-research/url_benchmark | A benchmark suite for unsupervised reinforcement learning agents, providing pre-trained models and scripts for testing and fine-tuning agent performance. | 335 |
| google-research/rlds | A toolkit for storing and manipulating episodic data in reinforcement learning and related tasks. | 302 |
 conglu1997/v-d4rl | Provides pre-built datasets and code for offline reinforcement learning from visual observations using deep learning algorithms | 94 |
 google-deepmind/rlax | A Python library providing reinforcement learning building blocks for implementing agent policies and functions | 1,272 |
 luchris429/purejaxrl | A high-performance implementation of reinforcement learning training pipelines using JAX and PyTorch-like functionality | 755 |
 geek-ai/magent | A platform for multi-agent reinforcement learning research and development | 1,700 |
 yg-smile/rl_vvc_dataset | A collection of benchmarks and implementations for testing reinforcement learning-based Volt-VAR control algorithms | 20 |
 rl-tools/rl-tools | An open-source C++ library for training reinforcement learning policies and controlling continuous-control environments. | 680 |
 araffin/rl-tutorial-jnrr19 | A tutorial project providing an introduction to reinforcement learning with Stable Baselines3 | 620 |
 alex-petrenko/sample-factory | A high-throughput reinforcement learning library with optimized synchronous and asynchronous implementations of policy gradients. | 839 |
 takuseno/d3rlpy | An open-source deep reinforcement learning library that supports offline and online training, providing an intuitive API for practitioners and researchers. | 1,349 |
 rlworkgroup/garage | A toolkit for developing and evaluating reinforcement learning algorithms in a reproducible manner | 1,893 |
 aunum/gold | A reinforcement learning library for Go, providing a set of agents to solve challenges in various environments. | 345 |
 glample/rnn-benchmarks | This project provides benchmarking results comparing various deep learning RNN implementations across different frameworks. | 169 |
 rle-foundation/rlexplore | Provides a unified toolkit for constructing, computing, and optimizing intrinsic reward modules in reinforcement learning | 373 |