There are 2 repositories under deep-rl topic.
Tutorials, assignments, and competitions for MIT Deep Learning related courses.
DeepTraffic is a deep reinforcement learning competition, part of the MIT Deep Learning series.
Pytorch code for ICLR-20 Paper "Learning to Explore using Active Neural SLAM"
A curated list of awesome Deep Reinforcement Learning resources.
CURL: Contrastive Unsupervised Representation Learning for Sample-Efficient Reinforcement Learning
Pytorch code for NeurIPS-20 Paper "Object Goal Navigation using Goal-Oriented Semantic Exploration"
:sparkles: A plotter for reinforcement learning (RL)
VR-Caps: A Virtual Environment for Active Capsule Endoscopy
Codes accompanying the paper "Believe What You See: Implicit Constraint Approach for Offline Multi-Agent Reinforcement Learning" (NeurIPS 2021 Spotlight https://arxiv.org/abs/2106.03400)
Accelerated minigrid environments with JAX
Recall to Imagine, a model-based RL algorithm with superhuman memory. Oral (1.2%) @ ICLR 2024
Mirror Descent Policy Optimization
A general model-free off-policy actor-critic implementation. Continuous and Discrete Soft Actor-Critic with multimodal observations, data augmentation, offline learning and behavioral cloning.
OpenAI团队的深度强化学习教程中文版
You can see a reference for Books, Articles, Courses and Educational Materials in this field. Implementation of Reinforcement Learning Algorithms and Environments. Python, OpenAI Gym, Tensorflow.
Deep Reinforcement Learning framework based on TensorFlow and OpenAI Gym
This repository implements the use of AI for robot tasks.
Implementation of Curiosity-Driven Exploration with PyTorch
Attend Before you Act: Leveraging human visual attention for continual learning
Code repository with classical reinforcement learning and deep reinforcement learning methods for Pokémon battles in Pokémon Showdown.
Code for NeurIPS 2023 paper Accountability in Offline Reinforcement Learning: Explaining Decisions with a Corpus of Examples
DRLA-eTGM
Deep RL for unsupervised hyperspectral band selection.
A curated list of awesome intelligent autonomous systems ecosystem
Deep Q-Learning algorithms to solve LunarLander-v2.
⚡️ Code and Notes 📝 for Grokking Deep RL and RL: An Introduction by Sutton & Barto(2nd edition, 2018) 🤘
Simple DQN implementation in jupyter notebook
My solution to the NeurIPS challenge Learn to Move: Walk Around
Exploration of deep reinforcement learning and various state-of-the-art techniques to create a turely autonomous agent.
Simple PyTorch implementation of the Vanilla Policy Gradient algorithm.