v-d4rl
Offline RL datasets
Provides pre-built datasets and code for offline reinforcement learning from visual observations using deep learning algorithms
Challenges and Opportunities in Offline Reinforcement Learning from Visual Observations
94 stars
4 watching
9 forks
Language: Python
last commit: over 1 year ago
Linked from 1 awesome list
Related projects:
| Repository | Description | Stars |
|---|---|---|
| | Provides exploratory data and algorithms for offline reinforcement learning in various control domains | 105 |
| | An open-source deep reinforcement learning library that supports offline and online training, providing an intuitive API for practitioners and researchers. | 1,349 |
| | A Python library for offline reinforcement learning research, providing datasets and utilities. | 310 |
| | Provides high-quality implementations of offline and offline-to-online reinforcement learning algorithms in Python. | 491 |
| | An offline deep reinforcement learning GUI tool that requires only datasets to operate and provides a powerful algorithm and intuitive interface. | 98 |
| | Provides benchmarking policies and datasets for offline reinforcement learning | 85 |
| | A collection of standardized environments and datasets for training and benchmarking algorithms in offline reinforcement learning | 1,371 |
| | A toolkit for storing and manipulating episodic data in reinforcement learning and related tasks. | 302 |
| | A collection of robotics datasets and simulated environments for training reinforcement learning algorithms on real robot hardware | 17 |
| | An open-source C++ library for training reinforcement learning policies and controlling continuous-control environments. | 680 |
| | A collection of benchmarks and implementations for testing reinforcement learning-based Volt-VAR control algorithms | 20 |
| | A Python library for offline reinforcement learning, evaluation, and policy selection in various environments. | 117 |
| | A high-performance implementation of reinforcement learning training pipelines using JAX and PyTorch-like functionality | 755 |
| | This library provides tools and algorithms for estimating the distribution correction in off-policy reinforcement learning problems | 99 |
| | A benchmark suite for unsupervised reinforcement learning agents, providing pre-trained models and scripts for testing and fine-tuning agent performance. | 335 |