Image de couverture de livre

Learning When to Act: Communication-Efficient Reinforcement Learning via Run-Time Assurance

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Haroon, Adam, Rodríguez-Seda, Erick J., Fleming, Cody, Schuler, Tristan
Format:	Preprint
Publié:	2026
Sujets:	Machine Learning Robotics
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Distributed Area Coverage with High Altitude Balloons Using Multi-Agent Reinforcement Learning
par: Haroon, Adam, et autres
Publié: (2025)

Flow-Based Single-Step Completion for Efficient and Expressive Policy Learning
par: Koirala, Prajwal, et autres
Publié: (2025)

Seasonal Station-Keeping of Short Duration High Altitude Balloons using Deep Reinforcement Learning
par: Schuler, Tristan K., et autres
Publié: (2025)

Towards Robust Car Following Dynamics Modeling via Blackbox Models: Methodology, Analysis, and Recommendations
par: Shahid, Muhammad Bilal, et autres
Publié: (2024)

When to Act, Ask, or Learn: Uncertainty-Aware Policy Steering
par: Yuan, Jessie, et autres
Publié: (2026)

ActSafe: Active Exploration with Safety Constraints for Reinforcement Learning
par: As, Yarden, et autres
Publié: (2024)

Transformer-based Multi-agent Reinforcement Learning for Separation Assurance in Structured and Unstructured Airspaces
par: Aziz, Arsyi, et autres
Publié: (2026)

Time Reversal Symmetry for Efficient Robotic Manipulations in Deep Reinforcement Learning
par: Jiang, Yunpeng, et autres
Publié: (2025)

Sample-Efficient Safety Assurances using Conformal Prediction
par: Luo, Rachel, et autres
Publié: (2021)

Reinforcement Learning with Elastic Time Steps
par: Wang, Dong, et autres
Publié: (2024)

Learning to Control DC Motor for Micromobility in Real Time with Reinforcement Learning
par: Poudel, Bibek, et autres
Publié: (2021)

Guided Data Augmentation for Offline Reinforcement Learning and Imitation Learning
par: Corrado, Nicholas E., et autres
Publié: (2023)

DreamerAD: Efficient Reinforcement Learning via Latent World Model for Autonomous Driving
par: Yang, Pengxuan, et autres
Publié: (2026)

Solving Robotics Tasks with Prior Demonstration via Exploration-Efficient Deep Reinforcement Learning
par: Shen, Chengyandan, et autres
Publié: (2025)

Data-Efficient Task Generalization via Probabilistic Model-based Meta Reinforcement Learning
par: Bhardwaj, Arjun, et autres
Publié: (2023)

Communication-Aware Reinforcement Learning for Cooperative Adaptive Cruise Control
par: Jiang, Sicong, et autres
Publié: (2024)

MOSEAC: Streamlined Variable Time Step Reinforcement Learning
par: Wang, Dong, et autres
Publié: (2024)

Solving Offline Reinforcement Learning with Decision Tree Regression
par: Koirala, Prajwal, et autres
Publié: (2024)

Sample-Efficient Diffusion-based Reinforcement Learning with Critic Guidance
par: Ding, Shutong, et autres
Publié: (2026)

Disentangled Unsupervised Skill Discovery for Efficient Hierarchical Reinforcement Learning
par: Hu, Jiaheng, et autres
Publié: (2024)

F1tenth Autonomous Racing With Offline Reinforcement Learning Methods
par: Koirala, Prajwal, et autres
Publié: (2024)

Robust Multi-Agent Reinforcement Learning for Small UAS Separation Assurance under GPS Degradation and Spoofing
par: Zongo, Alex, et autres
Publié: (2026)

SAC Flow: Sample-Efficient Reinforcement Learning of Flow-Based Policies via Velocity-Reparameterized Sequential Modeling
par: Zhang, Yixian, et autres
Publié: (2025)

Efficient Model-Based Reinforcement Learning Through Optimistic Thompson Sampling
par: Bayrooti, Jasmine, et autres
Publié: (2024)

Model-Based Reinforcement Learning for Control under Time-Varying Dynamics
par: Iten, Klemens, et autres
Publié: (2026)

ShieldNN: A Provably Safe NN Filter for Unsafe NN Controllers
par: Ferlez, James, et autres
Publié: (2020)

One Policy to Run Them All: an End-to-end Learning Approach to Multi-Embodiment Locomotion
par: Bohlinger, Nico, et autres
Publié: (2024)

Mechanistic Interpretability for Learning Assurance of a Vision-Based Landing System
par: Valentin, Romeo, et autres
Publié: (2026)

Efficient Reinforcement Learning by Guiding Generalist World Models with Non-Curated Data
par: Zhao, Yi, et autres
Publié: (2025)

Adaptive Outer-Loop Control of Quadrotors via Reinforcement Learning
par: Saj, Vishnu, et autres
Publié: (2026)

Apple: Toward General Active Perception via Reinforcement Learning
par: Schneider, Tim, et autres
Publié: (2025)

Data-Efficient Hierarchical Goal-Conditioned Reinforcement Learning via Normalizing Flows
par: Garg, Shaswat, et autres
Publié: (2026)

Efficient Multi-Task Reinforcement Learning via Task-Specific Action Correction
par: Feng, Jinyuan, et autres
Publié: (2024)

Priority-Driven Control and Communication in Decentralized Multi-Agent Systems via Reinforcement Learning
par: Guo, Qingyun, et autres
Publié: (2026)

When Should a Robot Think? Resource-Aware Reasoning via Reinforcement Learning for Embodied Robotic Decision-Making
par: Liu, Jun, et autres
Publié: (2026)

Handling Delay in Real-Time Reinforcement Learning
par: Anokhin, Ivan, et autres
Publié: (2025)

DRARL: Disengagement-Reason-Augmented Reinforcement Learning for Efficient Improvement of Autonomous Driving Policy
par: Zhou, Weitao, et autres
Publié: (2025)

Advancing Household Robotics: Deep Interactive Reinforcement Learning for Efficient Training and Enhanced Performance
par: Soni, Arpita, et autres
Publié: (2024)

Vision-Guided Outdoor Flight and Obstacle Evasion via Reinforcement Learning
par: Dutta, Shiladitya, et autres
Publié: (2026)

Robust Point Cloud Reinforcement Learning via PCA-Based Canonicalization
par: Bezick, Michael, et autres
Publié: (2025)