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
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Updated
Jul 10, 2022 - Python
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)
♟️ 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.
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
Gradient Free Reinforcement Learning solving Openai gym LunarLanderV2 by Evolution Strategy (Genetic Algorithm)
[ECC 2022] Codebase for the paper titled "Learning Eco-Driving Strategies at Signalized Intersections".
Neural Architecture Search for Convolutional Neural Networks using Reinforcement Learning
Implementation of Advantage-Actor-Critic for gym environments
Deep Reinforcement Learning Tutorial Site for PLDI 2019
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