#Reinforcement-learning-algorithms
Showing 36 of 36 repositories tagged #reinforcement-learning-algorithms, ranked by stars
PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
OpenDILab Decision AI Engine. The Most Comprehensive Reinforcement Learning Framework B.P.
Minimal implementation of clipped objective Proximal Policy Optimization (PPO) in PyTorch
OpenAI Gym environments for an open-source quadruped robot (SpotMicro)
NMA deep learning course
MDPs and POMDPs in Julia - An interface for defining, solving, and simulating fully and partially observable Markov decision processes on discrete and continuous spaces.
Contrib package for Stable-Baselines3 - Experimental reinforcement learning (RL) code
Code for paper "Computation Offloading Optimization for UAV-assisted Mobile Edge Computing: A Deep Deterministic Policy Gradient Approach"
A curated list of Monte Carlo tree search papers with implementations.
CURL: Contrastive Unsupervised Representation Learning for Sample-Efficient Reinforcement Learning
Guided Policy Search
Framework for Multi-Agent Deep Reinforcement Learning in Poker
The full collection of Jupyter Notebook labs from Andrew Ng's Machine Learning Specialization.
A PyTorch reinforcement learning library for generalizable and reproducible algorithm implementations with an aim to improve accessibility in RL
The Machine Learning project including ML/DL projects, notebooks, cheat codes of ML/DL, useful information on AI/AGI and codes or snippets/scripts/tasks with tips.
This is a repository which contains all my work related Machine Learning, AI and Data Science. This includes my graduate projects, machine learning competition codes, algorithm implementations and reading material.
Online Deep Learning: Learning Deep Neural Networks on the Fly / Non-linear Contextual Bandit Algorithm (ONN_THS)
Trading environnement for RL agents, backtesting and training.
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 comprehensive guide to Reinforcement Learning
Solve BipedalWalkerHardcore-v2 with TD3
Scalable Implementation of Neural Fictitous Self-Play
Collection of Deep Reinforcement Learning Algorithms implemented in PyTorch.
The GOLang implementation of NeuroEvolution of Augmented Topologies (NEAT) method to evolve and train Artificial Neural Networks without error back propagation
Upside-Down Reinforcement Learning (⅂ꓤ) implementation in PyTorch. Based on the paper published by Jürgen Schmidhuber.
ReinforceUI-Studio. A Python-based application designed to simplify the configuration and monitoring of RL training processes. Supporting MuJoCo, OpenAI Gymnasium, and DeepMind Control Suite. Algorithms included: CTD4, DDPG, DQN, PPO, SAC, TD3, TQC
A curated list of awesome reinforcement courses, video lectures, books, library and many more.
Cheatsheet of Reinforcement Learning (Based on Sutton-Barto Book - 2nd Edition)
ML-AI Community | Open Source | Built in Bharat for the World | Data science problem statements and solutions
ICML 2025 Papers: Dive into cutting-edge research from the premier machine learning conference. Stay current with breakthroughs in deep learning, generative AI, optimization, reinforcement learning, and beyond. Code implementations included. ⭐ support the future of machine learning research!
Gym environment which simulates intraday trading
End-to-end RL trading framework with PPO agent, self-attention neural network, custom Gym environment, and advanced backtesting.
Algorithmic Trading Using Deep Reinforcement Learning algorithms (PPO and DQN)
Indoor navigation using deep Q reinforcement learning
The Symbiotic Core Library provides a framework of ethical principles, practical modules, and grounded research to guide AI development, deployment and inferencing.
Financial market analysis using time-series models, clustering algorithms, Transformers, and reinforcement learning for trading strategies.