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A wrapper framework for Reinforcement Learning in the Webots robot simulator using Python 3.

This is a DRL(Deep Reinforcement Learning) platform built with Gazebo for the purpose of robot's adaptive path planning.

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

Simple renderer for use with MuJoCo (>=2.1.2) Python Bindings.

这是一个学习强化学习基础原理的仓库，主要包括了《深入浅出强化学习原理入门》书中一些例子和课后作业的代码

FlashSAC: Fast and Stable Off-Policy Reinforcement Learning for High-Dimensional Robot Control

A list of recent papers regarding dialogue generation

This code is written for the blogs

Online Goal-Conditioned Reinforcement Learning in JAX. ICLR 2025 Spotlight.

VARGPT-v1.1: Improve Visual Autoregressive Large Unified Model via Iterative Instruction Tuning and Reinforcement Learning