Highlights
- Pro
🏋️♂️ Reinforcement Learning
🐋 Simple implementations of various popular Deep Reinforcement Learning algorithms using TensorFlow2
High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)
Evotorch is a neuro-evolution library written in Python that makes use of the Pytorch library formalism. It allows the evolution of multilayer and convolutional networks. This project was conceived…
A mini library for Policy Gradients with Parameter-based Exploration, with reference implementation of the ClipUp optimizer (https://arxiv.org/abs/2008.02387) from NNAISENSE.
Minimal implementation of clipped objective Proximal Policy Optimization (PPO) in PyTorch
Implementation of RLHF (Reinforcement Learning with Human Feedback) on top of the PaLM architecture. Basically ChatGPT but with PaLM
A toolkit for developing and comparing reinforcement learning algorithms.
The most simple, flexible, and comprehensive OpenAI Gym trading environment (Approved by OpenAI Gym)
Season 3 of @twosigma's artificial intelligence programming challenge
PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
High-quality single-file implementations of SOTA Offline and Offline-to-Online RL algorithms: AWAC, BC, CQL, DT, EDAC, IQL, SAC-N, TD3+BC, LB-SAC, SPOT, Cal-QL, ReBRAC
An elegant PyTorch offline reinforcement learning library for researchers.
Using Deep Reinforcement Learning (associated with Deep Learning) to control a swarm of drones for dynamic area maximization problem
Mastering Diverse Domains through World Models
Efficient Batched Reinforcement Learning in TensorFlow
[NeurIPS 2022 Oral] The official implementation of POR in "A Policy-Guided Imitation Approach for Offline Reinforcement Learning"
Official PyTorch implementation of "Uncertainty-Based Offline Reinforcement Learning with Diversified Q-Ensemble" (NeurIPS'21)
PyTorch implementation of the Offline Reinforcement Learning algorithm CQL. Includes the versions DQN-CQL and SAC-CQL for discrete and continuous action spaces.
Code release for Efficient Planning in a Compact Latent Action Space (ICLR2023) https://arxiv.org/abs/2208.10291.
Python interface for accessing the near real-world offline reinforcement learning (NeoRL) benchmark datasets
A collection of offline reinforcement learning algorithms.
Minimal implementation of Decision Transformer: Reinforcement Learning via Sequence Modeling in PyTorch for mujoco control tasks in OpenAI gym
Latent Imagination Facilitates Zero-Shot Transfer in Autonomous Racing