Copertina

RACER: Epistemic Risk-Sensitive RL Enables Fast Driving with Fewer Crashes

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Stachowicz, Kyle, Levine, Sergey
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Robotics Artificial Intelligence Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

METRA: Scalable Unsupervised RL with Metric-Aware Abstraction
di: Park, Seohong, et al.
Pubblicazione: (2023)

HIQL: Offline Goal-Conditioned RL with Latent States as Actions
di: Park, Seohong, et al.
Pubblicazione: (2023)

RACER: Rational Artificial Intelligence Car-following-model Enhanced by Reality
di: Li, Tianyi, et al.
Pubblicazione: (2023)

Posterior Behavioral Cloning: Pretraining BC Policies for Efficient RL Finetuning
di: Wagenmaker, Andrew, et al.
Pubblicazione: (2025)

Q-learning with Adjoint Matching
di: Li, Qiyang, et al.
Pubblicazione: (2026)

Foundation Policies with Hilbert Representations
di: Park, Seohong, et al.
Pubblicazione: (2024)

Reinforcement Learning with Action Chunking
di: Li, Qiyang, et al.
Pubblicazione: (2025)

Decoupled Q-Chunking
di: Li, Qiyang, et al.
Pubblicazione: (2025)

Beyond Sight: Finetuning Generalist Robot Policies with Heterogeneous Sensors via Language Grounding
di: Jones, Joshua, et al.
Pubblicazione: (2025)

Real-Time Execution of Action Chunking Flow Policies
di: Black, Kevin, et al.
Pubblicazione: (2025)

RLDG: Robotic Generalist Policy Distillation via Reinforcement Learning
di: Xu, Charles, et al.
Pubblicazione: (2024)

CtRL-Sim: Reactive and Controllable Driving Agents with Offline Reinforcement Learning
di: Rowe, Luke, et al.
Pubblicazione: (2024)

Learning to Drive Anywhere with Model-Based Reannotation
di: Hirose, Noriaki, et al.
Pubblicazione: (2025)

Driving Through Uncertainty: Risk-Averse Control with LLM Commonsense for Autonomous Driving under Perception Deficits
di: Hu, Yuting, et al.
Pubblicazione: (2025)

SELFI: Autonomous Self-Improvement with Reinforcement Learning for Social Navigation
di: Hirose, Noriaki, et al.
Pubblicazione: (2024)

Reflective Planning: Vision-Language Models for Multi-Stage Long-Horizon Robotic Manipulation
di: Feng, Yunhai, et al.
Pubblicazione: (2025)

Don't Freeze, Don't Crash: Extending the Safe Operating Range of Neural Navigation in Dense Crowds
di: Zhang, Jiefu, et al.
Pubblicazione: (2026)

KALIE: Fine-Tuning Vision-Language Models for Open-World Manipulation without Robot Data
di: Tang, Grace, et al.
Pubblicazione: (2024)

Fusing Driver Perceived and Physical Risk for Safety Critical Scenario Screening in Autonomous Driving
di: Xiong, Chen, et al.
Pubblicazione: (2026)

Ethics-Aware Safe Reinforcement Learning for Rare-Event Risk Control in Interactive Urban Driving
di: Li, Dianzhao, et al.
Pubblicazione: (2025)

SEAL: Towards Safe Autonomous Driving via Skill-Enabled Adversary Learning for Closed-Loop Scenario Generation
di: Stoler, Benjamin, et al.
Pubblicazione: (2024)

Automatic Environment Shaping is the Next Frontier in RL
di: Park, Younghyo, et al.
Pubblicazione: (2024)

Yell At Your Robot: Improving On-the-Fly from Language Corrections
di: Shi, Lucy Xiaoyang, et al.
Pubblicazione: (2024)

Language-Conditioned Offline RL for Multi-Robot Navigation
di: Morad, Steven, et al.
Pubblicazione: (2024)

Sample-efficient and Scalable Exploration in Continuous-Time RL
di: Iten, Klemens, et al.
Pubblicazione: (2025)

Investigating Memory in Model-Free RL with POPGym Arcade
di: Wang, Zekang, et al.
Pubblicazione: (2025)

GRAM: Generalization in Deep RL with a Robust Adaptation Module
di: Queeney, James, et al.
Pubblicazione: (2024)

First Order Model-Based RL through Decoupled Backpropagation
di: Amigo, Joseph, et al.
Pubblicazione: (2025)

CaRL: Learning Scalable Planning Policies with Simple Rewards
di: Jaeger, Bernhard, et al.
Pubblicazione: (2025)

Dual RL: Unification and New Methods for Reinforcement and Imitation Learning
di: Sikchi, Harshit, et al.
Pubblicazione: (2023)

Generalised Linear Models in Deep Bayesian RL with Learnable Basis Functions
di: You, Jingyang, et al.
Pubblicazione: (2025)

Enhancing RL Generalizability in Robotics through SHAP Analysis of Algorithms and Hyperparameters
di: Kong, Lingxiao, et al.
Pubblicazione: (2026)

RL-100: Performant Robotic Manipulation with Real-World Reinforcement Learning
di: Lei, Kun, et al.
Pubblicazione: (2025)

DEAS: DEtached value learning with Action Sequence for Scalable Offline RL
di: Kim, Changyeon, et al.
Pubblicazione: (2025)

ARC-RL: A Reinforcement Learning Playground Inspired by ARC Raiders
di: Romeo, Carlo, et al.
Pubblicazione: (2026)

RACER: Risk-Aware Calibrated Efficient Routing for Large Language Models
di: Hao, Sai, et al.
Pubblicazione: (2026)

NDST: Neural Driving Style Transfer for Human-Like Vision-Based Autonomous Driving
di: Kim, Donghyun, et al.
Pubblicazione: (2024)

Performance Comparison of Deep RL Algorithms for Mixed Traffic Cooperative Lane-Changing
di: Yao, Xue, et al.
Pubblicazione: (2024)

A Review of Online Diffusion Policy RL Algorithms for Scalable Robotic Control
di: Choi, Wonhyeok, et al.
Pubblicazione: (2026)

Efficient Online RL Fine Tuning with Offline Pre-trained Policy Only
di: Xiao, Wei, et al.
Pubblicazione: (2025)