maze
RL Framework
An RL framework for building and training reinforcement learning models in Python
Maze Applied Reinforcement Learning Framework
266 stars
6 watching
12 forks
Language: Python
last commit: 3 months ago
Linked from 2 awesome lists
applied-machine-learningautomationdata-sciencedecision-makingdeep-learningdistributeddocumentationframeworkmachine-learningmonitoringoptimizationpythonreinforcement-learningsimulation
Related projects:
Repository | Description | Stars |
---|---|---|
| A framework for implementing complex reinforcement learning algorithms with flexibility and ease of implementation | 306 |
| A collection of implementations of Reinforcement Learning and planning algorithms in Python. | 596 |
| A collection of implementations of reinforcement learning algorithms in MATLAB | 61 |
| A high-performance implementation of reinforcement learning training pipelines using JAX and PyTorch-like functionality | 755 |
| A framework for parallel population-based reinforcement learning | 507 |
| An open-source reinforcement learning framework for autonomous driving tasks using the Carla-Simulator environment and Ray/Rllib libraries. | 35 |
| A Python implementation of a deep reinforcement learning algorithm combining multiple techniques for improved performance in Atari games | 1,591 |
| A Python library implementing state-of-the-art deep reinforcement learning algorithms for Keras and OpenAI Gym environments. | 8 |
| A high-throughput reinforcement learning library with optimized synchronous and asynchronous implementations of policy gradients. | 839 |
| A reinforcement learning library for Go, providing a set of agents to solve challenges in various environments. | 345 |
| A framework for simulating and evaluating reinforcement learning from human feedback methods | 786 |
| A modular framework for building reinforcement learning agents in Python using Gymnasium and JAX. | 168 |
| A Python library for reinforcement learning algorithms and environments. | 824 |
| Replication of Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks in PyTorch for reinforcement learning tasks | 830 |
| An environment designed to test and train reinforcement learning algorithms in a flexible, procedurally generated 2D space with various objects and interactions. | 369 |