zhouzhiqian's repositories
ALN-DSAC
The code is for paper "Representation Learning and Reinforcement Learning for Dynamic Complex Motion Planning System".
ChatPaper
Use ChatGPT to summarize the arXiv papers. 全流程加速科研,利用chatgpt进行论文总结+润色+审稿+审稿回复
CrowdNav_DSRNN
[ICRA 2021] Decentralized Structural-RNN for Robot Crowd Navigation with Deep Reinforcement Learning
DePO
Code for ICML 2022 paper "Plan Your Target and Learn Your Skills: Transferable State-Only Imitation Learning via Decoupled Policy Optimization"
DRL-code-pytorch
Concise pytorch implements of DRL algorithms, including REINFORCE, A2C, DQN, PPO(discrete and continuous), DDPG, TD3, SAC.
EMO-RL-UAV
The Python implementation of the proposed framework in the paper Evolutionary Multi-Objective Deep Reinforcement Learning for Autonomous UAV Navigation in Large-Scale Complex Environments
EqMotion
[CVPR2023] EqMotion: Equivariant Multi-agent Motion Prediction with Invariant Interaction Reasoning
fpl
Code/data of the paper "Future Person Localization in First-Person Videos" (CVPR2018)
intrinsic-rewards-navigation
Repository of the work: Improving robot navigation in crowded environments using intrinsic rewards (ICRA 2023)
Off-Policy-TRC
Official GitHub Repository for Efficient Off-Policy Safe Reinforcement Learning Using Trust Region Conditional Value At Risk.
rl_with_resets
JAX implementation of deep RL agents with resets from the paper "The Primacy Bias in Deep Reinforcement Learning"
Safe-Policy-Optimization
This is a benchmark repository for safe reinforcement learning algorithms
Safe-Reinforcement-Learning-Baselines
The repository is for safe reinforcement learning baselines.
SafeDreamer
ICLR 2024: SafeDreamer: Safe Reinforcement Learning with World Models
sngnnv2
SNNGNN-V2
SocialGym2
SocialGym 2: A lightweight benchmark and simulator for multi-robot social navigation using ROS and the OpenAI gym.
TD7
Author's PyTorch implementation of TD7 for online and offline RL
WCSAC
Code for the paper "WCSAC: Worst-Case Soft Actor Critic for Safety-Constrained Reinforcement Learning"