#Deep-reinforcement-learning
Showing 60 of 158 repositories tagged #deep-reinforcement-learning, ranked by stars
Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.
The Unity Machine Learning Agents Toolkit (ML-Agents) is an open-source project that enables games and simulations to serve as environments for training intelligent agents using deep reinforcement learning and imitation learning.
Open source simulator for autonomous vehicles built on Unreal Engine / Unity, from Microsoft AI & Research
FinRLยฎ: Financial Reinforcement Learning. ๐ฅ
Open-source simulator for autonomous driving research.
Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!
Tutorials, assignments, and competitions for MIT Deep Learning related courses.
High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)
(โโ _โ ) - Deep Reinforcement Learning instrumenting bettercap for WiFi pwning.
Lab Materials for MIT 6.S191: Introduction to Deep Learning
Trax โ Deep Learning with Clear Code and Speed
Flappy Bird hack using Deep Reinforcement Learning (Deep Q-learning).
A course in reinforcement learning in the wild
This repo contains the Hugging Face Deep Reinforcement Learning Course.
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 ....
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A curated list of reinforcement learning with human feedback resources (continually updated)
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
Minimal and Clean Reinforcement Learning Examples
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)
Open source neural network chess engine with GPU acceleration and broad hardware support.
A modular high-level library to train embodied AI agents across a variety of tasks and environments.
MuZero
Summaries of machine learning papers
Minimal implementation of clipped objective Proximal Policy Optimization (PPO) in PyTorch
Deep Reinforcement Learning: Zero to Hero!
List of awesome resources for machine learning-based algorithmic trading
FinRLยญยฎ-Meta: Dynamic datasets and market environments for FinRL.
DeepTraffic is a deep reinforcement learning competition, part of the MIT Deep Learning series.
Playing the game of snake with AI.
Top 200 deep learning Github repositories sorted by the number of stars.
Rainbow: Combining Improvements in Deep Reinforcement Learning
An offline deep reinforcement learning library
[ICML 2017] TensorFlow code for Curiosity-driven Exploration for Deep Reinforcement Learning
Softlearning is a reinforcement learning framework for training maximum entropy policies in continuous domains. Includes the official implementation of the Soft Actor-Critic algorithm.
An artificial intelligence platform for the StarCraft II with large-scale distributed training and grand-master agents.
PyTorch implementation of Asynchronous Advantage Actor Critic (A3C) from "Asynchronous Methods for Deep Reinforcement Learning".
Deep Reinforcement Learning for mobile robot navigation in ROS Gazebo simulator. Using Twin Delayed Deep Deterministic Policy Gradient (TD3) neural network, a robot learns to navigate to a random goal point in a simulated environment while avoiding obstacles.
Minimal Deep Q Learning (DQN & DDQN) implementations in Keras
Train robotic agents to learn to plan pushing and grasping actions for manipulation with deep reinforcement learning.
Contains high quality implementations of Deep Reinforcement Learning algorithms written in PyTorch
PyGame Learning Environment (PLE) -- Reinforcement Learning Environment in Python.
Grokking Deep Reinforcement Learning
Deep Reinforcement Learning toolkit: record and replay cryptocurrency limit order book data & train a DDQN agent
Reinforcement learning environments with musculoskeletal models
PyTorch implementation of soft actor critic
Gibson Environments: Real-World Perception for Embodied Agents
Python library for Reinforcement Learning.
Streamlining reinforcement learning with RLOps. State-of-the-art RL algorithms and tools, with 10x faster training through evolutionary hyperparameter optimization.
Deepdrive is a simulator that allows anyone with a PC to push the state-of-the-art in self-driving
Pytorch code for ICLR-20 Paper "Learning to Explore using Active Neural SLAM"
Deep Reinforcement Learning with pytorch & visdom
Reinforcement Learning Tutorial with Demo: DP (Policy and Value Iteration), Monte Carlo, TD Learning (SARSA, QLearning), Function Approximation, Policy Gradient, DQN, Imitation, Meta Learning, Papers, Courses, etc..
Deep Reinforcement Learning based Trading Agent for Bitcoin
JAX (Flax) implementation of algorithms for Deep Reinforcement Learning with continuous action spaces.
StarCraft II - pysc2 Deep Reinforcement Learning Examples
TensorFlow and Deep Learning Tutorials