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)
♟️ 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.
(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>
High-fidelity cartpole environment for reinforcement learning
[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
This repository is for practicing the basics of Reinforcement Learning.
During my Course of Ai in kiet. I was learing reinforce learning algorithm. I have implemented Q-Learnning on Frozen Lake. Great game/ also make ppt for describe code
Gym Armed Bandits is an environment bundle for OpenAI Gym
A novel approach to solve Contextual Reinforcement Learning
Kya kre ga jan kr
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