Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
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A standard API for single-agent reinforcement learning environments, with popular reference environments and related utilities (formerly Gym)
OpenDILab Decision AI Engine. The Most Comprehensive Reinforcement Learning Framework B.P.
- reinforcement-learning
- multiagent-reinforcement-learning
- self-play
- imitation-learning
A modular, primitive-first, python-first PyTorch library for Reinforcement Learning.
- ai
- control
- decision-making
- distributed-computing
A standard API for multi-agent reinforcement learning environments, with popular reference environments and related utilities
- api
- gymnasium
- multi-agent-reinforcement-learning
- reinforcement-learning
A high-performance distributed training framework for Reinforcement Learning
- reinforcement-learning
- large-scale
- parallelization
An experimentation and research platform to investigate the interaction of automated agents in an abstract simulated network environments.
Modular Reinforcement Learning (RL) library (implemented in PyTorch, JAX, and NVIDIA Warp) with support for Gymnasium/Gym, NVIDIA Isaac Lab, MuJoCo Playground and other environments
- reinforcement-learning
- python
- deep-learning
- gym
Reinforcement learning library(framework) designed for PyTorch, implements DQN, DDPG, A2C, PPO, SAC, MADDPG, A3C, APEX, IMPALA ...
- reinforcement-learning
- deep-learning
- pytorch
- pytorch-reinforcement-learning
Every day, millions of traders around the world are trying to make money by trading stocks. These days, physical traders are also being replaced by automated trading robots. Algorithmic trading market has experienced significant growth rate and large number of firms are using it. I have tried to build a Deep Q-learning reinforcement agent model to do automated stock trading.
Maze Applied Reinforcement Learning Framework