Carla_Ray_Rlib
RL framework
An open-source reinforcement learning framework for autonomous driving tasks using the Carla-Simulator environment and Ray/Rllib libraries.
Carla-Simulator environment compatible with Ray/Rllib
35 stars
2 watching
12 forks
Language: Python
last commit: over 5 years ago
Linked from 1 awesome list
Related projects:
Repository | Description | Stars |
---|---|---|
| Provides a framework for using CARLA as a reinforcement learning environment | 95 |
| A high-performance implementation of reinforcement learning training pipelines using JAX and PyTorch-like functionality | 755 |
| A Reinforcement Learning project for training an autonomous driving agent in a simulated environment using the Carla game engine | 368 |
| An implementation of an actor-critic reinforcement learning algorithm in Python. | 245 |
| A framework for implementing complex reinforcement learning algorithms with flexibility and ease of implementation | 306 |
| An RL framework for building and training reinforcement learning models in Python | 266 |
| A Python implementation of a deep reinforcement learning algorithm combining multiple techniques for improved performance in Atari games | 1,591 |
| A framework for simulating and evaluating reinforcement learning from human feedback methods | 786 |
| A research project developing personalized Advanced Driver Assistance Systems through reinforcement learning with human state metrics and CARLA Simulator | 4 |
| A Python library implementing state-of-the-art deep reinforcement learning algorithms for Keras and OpenAI Gym environments. | 8 |
| A framework for parallel population-based reinforcement learning | 507 |
| A collection of implementations of Reinforcement Learning and planning algorithms in Python. | 596 |
| A modular framework for building reinforcement learning agents in Python using Gymnasium and JAX. | 168 |
| A collection of implementations of reinforcement learning algorithms in MATLAB | 61 |
| A reinforcement learning project to train an autonomous driving agent in a simulated environment using a deep learning approach | 230 |