#Ppo
Showing 42 of 42 repositories tagged #ppo, ranked by stars
An elegant PyTorch deep reinforcement learning library.
High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)
Simple Reinforcement learning tutorials, 莫烦Python 中文AI教学
Learn Deep Reinforcement Learning in 60 days! Lectures & Code in Python. Reinforcement Learning + Deep Learning
PyTorch implementation of DQN, AC, ACER, A2C, A3C, PG, DDPG, TRPO, PPO, SAC, TD3 and ....
PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKTR) and Generative Adversarial Imitation Learning (GAIL).
Implementations from the free course Deep Reinforcement Learning with Tensorflow and PyTorch
Clean, Robust, and Unified PyTorch implementation of popular Deep Reinforcement Learning (DRL) algorithms (Q-learning, Duel DDQN, PER, C51, Noisy DQN, PPO, DDPG, TD3, SAC, ASL)
Implementations of basic RL algorithms with minimal lines of codes! (pytorch based)
Minimal implementation of clipped objective Proximal Policy Optimization (PPO) in PyTorch
Proximal Policy Optimization (PPO) algorithm for Super Mario Bros
Contains high quality implementations of Deep Reinforcement Learning algorithms written in PyTorch
This repository contains most of pytorch implementation based classic deep reinforcement learning algorithms, including - DQN, DDQN, Dueling Network, DDPG, SAC, A2C, PPO, TRPO. (More algorithms are still in progress)
🌾 OAT: A research-friendly framework for LLM online alignment, including reinforcement learning, preference learning, etc.
Easy and Efficient Finetuning LLMs. (Supported LLama, LLama2, LLama3, Qwen, Baichuan, GLM , Falcon) 大模型高效量化训练+部署.
🐋 Simple implementations of various popular Deep Reinforcement Learning algorithms using TensorFlow2
Deep Reinforcement Learning (PPO) in Autonomous Driving (Carla) [from scratch]
Long-Term Evolution Project of Reinforcement Learning
LLM Tuning with PEFT (SFT+RM+PPO+DPO with LoRA)
lagom: A PyTorch infrastructure for rapid prototyping of reinforcement learning algorithms.
Trading Environment(OpenAI Gym) + PPO(TensorForce)
LLaMA-TRL: Fine-tuning LLaMA with PPO and LoRA
A full pipeline to finetune Vicuna LLM with LoRA and RLHF on consumer hardware. Implementation of RLHF (Reinforcement Learning with Human Feedback) on top of the Vicuna architecture. Basically ChatGPT but with Vicuna
Train a neural network to PvP in Old School RuneScape using reinforcement learning.
chatglm-6b微调/LORA/PPO/推理, 样本为自动生成的整数/小数加减乘除运算, 可gpu/cpu
A collection of various RL algorithms like policy gradients, DQN and PPO. The goal of this repo will be to make it a go-to resource for learning about RL. How to visualize, debug and solve RL problems. I've additionally included playground.py for learning more about OpenAI gym, etc.
A custom MARL (multi-agent reinforcement learning) environment where multiple agents trade against one another (self-play) in a zero-sum continuous double auction. Ray [RLlib] is used for training.
A full pipeline to finetune ChatGLM LLM with LoRA and RLHF on consumer hardware. Implementation of RLHF (Reinforcement Learning with Human Feedback) on top of the ChatGLM architecture. Basically ChatGPT but with ChatGLM
A comprehensive guide to Reinforcement Learning
Explorer is a PyTorch reinforcement learning framework for exploring new ideas.
逐行对照 MiniMind 源码精读、并延伸到大模型技术体系的中文学习笔记 —— 预训练 / SFT / DPO / PPO / GRPO、训练机制、MiniMind2→3 版本对照、真实实验证据。
The simplest implementation of Pensieve (SIGCOMM' 17) via state-of-the-art RL algorithms, including PPO, DQN, SAC, and support for both TensorFlow and PyTorch.
Collection of Deep Reinforcement Learning Algorithms implemented in PyTorch.
A travel agent based on Qwen2.5, fine-tuned by SFT + DPO/PPO/GRPO using traveling question-answer dataset, a mindmap can be output using the response. A RAG system is build upon the tuned qwen2, using Prompt-Template + Tool-Use + Chroma embedding database + LangChain
A RL approach to enable cost-effective, intelligent interactions between a local agent and a remote LLM
Curated, opinionated index of post-R1 LLM × Reinforcement Learning. Many deep-dive blog posts cross-linked to many papers — GRPO, DAPO, DPO, PPO, RLHF, GSPO, CISPO, VAPO, Reward Modeling, MoE RL stability, Verifier-Free RL, Training-Free RL, Agentic RL, DeepSeek-R1 reproduction.
A full pipeline to finetune Alpaca LLM with LoRA and RLHF on consumer hardware. Implementation of RLHF (Reinforcement Learning with Human Feedback) on top of the Alpaca architecture. Basically ChatGPT but with Alpaca
Our NIPS 2017: Learning to Run source code
Portfolio management using Actor-Critic Deep Reinforcement Learning algorithms including A2C, DDPG, and PPO
Algorithmic Trading Using Deep Reinforcement Learning algorithms (PPO and DQN)
RL stock selection for China A-share — bundled polars-native factor library (105 Alpha101 + 191 GTJA Alpha191 = 296 factors), board-aware price limits, GPU train + ONNX CPU infer, MIT-licensed.
