Train deep reinforcement learning model for robotics grasping. Choose from different perception layers raw Depth, RGBD and autoencoder. Test the learned models in different scenes and object datasets

Monitoring recent cross-research on LLM & RL on arXiv for control. If there are good papers, PRs are welcome.

Population-Based Training (PBT) for Reinforcement Learning using Message Passing Interface (MPI)

Berkeley CS285 2019 homework solution

DistRL: An Asynchronous Distributed Reinforcement Learning Framework for On-Device Control Agents

♟️ Deploy a AI five-in-a-row game. Including front-end, back-end & deep RL code. 基于 vue3 与 flask 部署的强化学习五子棋 AlphaGo 实践。

My implementation of Hindsight replay in PyTorch: "Hindsight Experience Replay"

Q-learning project where an agent learns by himself to find the exit inside a maze. The project is implemented as a level-based game.

[ECC 2022] Codebase for the paper titled "Learning Eco-Driving Strategies at Signalized Intersections".

JS smart crawler using reinforcement learning

RLjs currently serves as an interactive playground for learning reinforcement learning.

(Explainable) Algorithmic Recourse with Reinforcement Learning and MCTS (FARE and E-FARE)

Reinforcement learning with pytorch

Code for <Traceable Automatic Feature Transformation via Cascading Actor-Critic Agents>

Multiple Generation Based Knowledge Distillation: A Roadmap

Code for Prediction and Planning Under Uncertainty (PPUU) in an Autonomous Ferry Navigation setting

High-fidelity cartpole environment for reinforcement learning

Gradient Free Reinforcement Learning solving Openai gym LunarLanderV2 by Evolution Strategy (Genetic Algorithm)

Neural Architecture Search for Convolutional Neural Networks using Reinforcement Learning