(Re)$^2$H2O: Autonomous Driving Scenario Generation via Reversely
Regularized Hybrid Offline-and-Online Reinforcement Learning

(Re) $^2$ H2O: Autonomous Driving Scenario Generation via Reversely Regularized Hybrid Offline-and-Online Reinforcement Learning

27 February 2023

Haoyi Niu

Jianming Hu

Papers citing "(Re)$^2$H2O: Autonomous Driving Scenario Generation via Reversely Regularized Hybrid Offline-and-Online Reinforcement Learning"

7 / 7 papers shown

Title
Adversarial and Reactive Traffic Entities for Behavior-Realistic Driving Simulation: A Review Joshua Ransiek Philipp Reis Tobias Schürmann Eric Sax 75 0 0 21 Sep 2024
Benchmarks for Reinforcement Learning with Biased Offline Data and Imperfect Simulators Ori Linial Guy Tennenholtz Uri Shalit OffRL 40 1 0 30 Jun 2024
Dynamically Expanding Capacity of Autonomous Driving with Near-Miss Focused Training Framework Ziyuan Yang Zhaoyang Li Jianming Hu Yi Zhang 27 0 0 05 Jun 2024
Data-driven Traffic Simulation: A Comprehensive Review Di Chen Meixin Zhu H. Yang Xuesong Wang Yinhai Wang 26 26 0 24 Oct 2023
Stackelberg Driver Model for Continual Policy Improvement in Scenario-Based Closed-Loop Autonomous Driving Haoyi Niu Qimao Chen Yingyue Li Yi Zhang Jianming Hu 40 3 0 25 Sep 2023
Continual Driving Policy Optimization with Closed-Loop Individualized Curricula Haoyi Niu Yi Tian Xu Xingjian Jiang Jianming Hu 33 3 0 25 Sep 2023
TrafficSim: Learning to Simulate Realistic Multi-Agent Behaviors Simon Suo S. Regalado Sergio Casas R. Urtasun 151 224 0 17 Jan 2021