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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Playing Pokemon Red with Reinforcement Learning
Massively Parallel Deep Reinforcement Learning. 🔥
- pytorch
- reinforcement-learning
- ppo
- sac
An experimentation and research platform to investigate the interaction of automated agents in an abstract simulated network environments.
C++-based high-performance parallel environment execution engine (vectorized env) for general RL environments.
- reinforcement-learning
- parallel-processing
- cpp17
- pybind11
📈 Personae is a repo of implements and environment of Deep Reinforcement Learning & Supervised Learning for Quantitative Trading.
- reinforcement-learning
- supervised-learning
- stock-data
- trading
An engine for high performance multi-agent environments with very large numbers of agents, along with a set of reference environments
Gibson Environments: Real-World Perception for Embodied Agents
- computer-vision
- robotics
- simulator
- sim2real
A brain that learns from live experience. System 1 by default: perception, memory, plasticity and action. Optional System 2 for self-observation and slow corrections.
- machine-learning
- embodied-ai
- online-learning
- python
An OpenAI gym wrapper for CARLA simulator
- carla-simulator
- autonomous-driving
- deep-reinforcement-learning
- imitation-learning
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
HALO: Perceptive Humanoid Motion from Simulation
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.
Whole-body motion tracking for the Unitree G1 in about 3 minutes on one GPU.
- humanoid-robotics
- lafan1
- mjlab
- motion-tracking
A micro neural network multilayer perceptron for MicroPython (used on ESP32 and Pycom modules)
- micropython
- neural-network
- multilayer-perceptron
- mlp
Whole-body motion tracking for the Unitree G1 in under 3 minutes on average on one GPU: return 0.82 with 0/40 clips failed, held from 2.74 min (mean of 15 seeds, range 2.21-3.61, fine checkpoints), 11.87 it/s (world model + Muon + overlapped CUDA streams, mjlab)
- humanoid
- robot-learning
- supermimic
- world-model
A set of neuroevolution experiments with/towards deep networks
- rubyml
Python application to setup and run streaming (contextual) bandit experiments.
- streaming
- bandit
- mab
- cmab