Infrastructure for continually self‑improving agents
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Tensorflow implementation of Human-Level Control through Deep Reinforcement Learning
PGPortfolio: Policy Gradient Portfolio, the source code of "A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem"(https://arxiv.org/pdf/1706.10059.pdf).
Clean PyTorch implementations of imitation and reward learning algorithms
- reward-learning
- inverse-reinforcement-learning
- imitation-learning
- gymnasium
C++-based high-performance parallel environment execution engine (vectorized env) for general RL environments.
- reinforcement-learning
- parallel-processing
- cpp17
- pybind11
An engine for high performance multi-agent environments with very large numbers of agents, along with a set of reference environments
A light-weight deep reinforcement learning framework for portfolio management. This project explores the possibility of applying deep reinforcement learning algorithms to stock trading in a highly modular and scalable framework.
Reproduction of SuperMimic (arXiv:2610.28480): learned differentiable world model + BPTT policy for G1 humanoid motion tracking, on mjlab/MuJoCo Warp
Whole-body motion tracking for the Unitree G1 in about 3 minutes on one GPU.
- humanoid-robotics
- lafan1
- mjlab
- motion-tracking
Generative models for transcriptomic-driven or protein-driven molecular design (PaccMann^RL).
- deep-reinforcement-learning
- generative-model
- vae
- molecule-generation