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
Population-Based Training (PBT) for Reinforcement Learning using Message Passing Interface (MPI)
Monitoring recent cross-research on LLM & RL on arXiv for control. If there are good papers, PRs are welcome.
♟️ 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。
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.
My implementation of Hindsight replay in PyTorch: "Hindsight Experience Replay"
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
Gradient Free Reinforcement Learning solving Openai gym LunarLanderV2 by Evolution Strategy (Genetic Algorithm)
Code for <Traceable Automatic Feature Transformation via Cascading Actor-Critic Agents>
Code for Prediction and Planning Under Uncertainty (PPUU) in an Autonomous Ferry Navigation setting
Multiple Generation Based Knowledge Distillation: A Roadmap
[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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