Advancing Robustness in Deep Reinforcement Learning with an Ensemble Defense Approach
Fuente:
arXiv
Saved in:
| Main Authors: | Mohan, Adithya, Rößle, Dominik, Cremers, Daniel, Schön, Torsten |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Learning Expressive Priors for Generalization and Uncertainty Estimation in Neural Networks
by: Schnaus, Dominik, et al.
Published: (2023)
by: Schnaus, Dominik, et al.
Published: (2023)
DrivIng: A Large-Scale Multimodal Driving Dataset with Full Digital Twin Integration
by: Rößle, Dominik, et al.
Published: (2026)
by: Rößle, Dominik, et al.
Published: (2026)
Enhancing Robustness in Deep Reinforcement Learning: A Lyapunov Exponent Approach
by: Young, Rory, et al.
Published: (2024)
by: Young, Rory, et al.
Published: (2024)
Structure in Deep Reinforcement Learning: A Survey and Open Problems
by: Mohan, Aditya, et al.
Published: (2023)
by: Mohan, Aditya, et al.
Published: (2023)
UACER: An Uncertainty-Adaptive Critic Ensemble Framework for Robust Adversarial Reinforcement Learning
by: Wu, Jiaxi, et al.
Published: (2025)
by: Wu, Jiaxi, et al.
Published: (2025)
Towards Robust Policy: Enhancing Offline Reinforcement Learning with Adversarial Attacks and Defenses
by: Nguyen, Thanh, et al.
Published: (2024)
by: Nguyen, Thanh, et al.
Published: (2024)
Sparse Threats, Focused Defense: Criticality-Aware Robust Reinforcement Learning for Safe Autonomous Driving
by: Wei, Qi, et al.
Published: (2026)
by: Wei, Qi, et al.
Published: (2026)
Regret-Based Defense in Adversarial Reinforcement Learning
by: Belaire, Roman, et al.
Published: (2023)
by: Belaire, Roman, et al.
Published: (2023)
Real-Time Evaluation of Autonomous Systems under Adversarial Attacks
by: Mohan, Adithya, et al.
Published: (2026)
by: Mohan, Adithya, et al.
Published: (2026)
Robust Deep Reinforcement Learning against Adversarial Behavior Manipulation
by: Yamabe, Shojiro, et al.
Published: (2024)
by: Yamabe, Shojiro, et al.
Published: (2024)
RLAE: Reinforcement Learning-Assisted Ensemble for LLMs
by: Fu, Yuqian, et al.
Published: (2025)
by: Fu, Yuqian, et al.
Published: (2025)
Federated Ensemble-Directed Offline Reinforcement Learning
by: Rengarajan, Desik, et al.
Published: (2023)
by: Rengarajan, Desik, et al.
Published: (2023)
Diverse Projection Ensembles for Distributional Reinforcement Learning
by: Zanger, Moritz A., et al.
Published: (2023)
by: Zanger, Moritz A., et al.
Published: (2023)
Learning Tennis Strategy Through Curriculum-Based Dueling Double Deep Q-Networks
by: Mohan, Vishnu
Published: (2025)
by: Mohan, Vishnu
Published: (2025)
The EarlyBird Gets the WORM: Heuristically Accelerating EarlyBird Convergence
by: Vasudev, Adithya
Published: (2024)
by: Vasudev, Adithya
Published: (2024)
Generative Modeling for Robust Deep Reinforcement Learning on the Traveling Salesman Problem
by: Li, Michael, et al.
Published: (2025)
by: Li, Michael, et al.
Published: (2025)
Towards Robust Deep Reinforcement Learning against Environmental State Perturbation
by: Wang, Chenxu, et al.
Published: (2025)
by: Wang, Chenxu, et al.
Published: (2025)
Robust Deep Reinforcement Learning with Adaptive Adversarial Perturbations in Action Space
by: Liu, Qianmei, et al.
Published: (2024)
by: Liu, Qianmei, et al.
Published: (2024)
CEAR: Certified Ensemble Adversarial Robustness in DNNs
by: Sadig, Daniel, et al.
Published: (2026)
by: Sadig, Daniel, et al.
Published: (2026)
Advancing Forest Fire Prevention: Deep Reinforcement Learning for Effective Firebreak Placement
by: Murray, Lucas, et al.
Published: (2024)
by: Murray, Lucas, et al.
Published: (2024)
Advancing Investment Frontiers: Industry-grade Deep Reinforcement Learning for Portfolio Optimization
by: Ndikum, Philip, et al.
Published: (2024)
by: Ndikum, Philip, et al.
Published: (2024)
DeepDefense: Layer-Wise Gradient-Feature Alignment for Building Robust Neural Networks
by: Lin, Ci, et al.
Published: (2025)
by: Lin, Ci, et al.
Published: (2025)
Enhancing Security in Deep Reinforcement Learning: A Comprehensive Survey on Adversarial Attacks and Defenses
by: Yichao, Wu, et al.
Published: (2025)
by: Yichao, Wu, et al.
Published: (2025)
A Dual-Agent Adversarial Framework for Robust Generalization in Deep Reinforcement Learning
by: Xie, Zhengpeng, et al.
Published: (2025)
by: Xie, Zhengpeng, et al.
Published: (2025)
Robust Deep Reinforcement Learning Through Adversarial Attacks and Training : A Survey
by: Schott, Lucas, et al.
Published: (2024)
by: Schott, Lucas, et al.
Published: (2024)
Tradeoffs When Considering Deep Reinforcement Learning for Contingency Management in Advanced Air Mobility
by: Alvarez, Luis E., et al.
Published: (2024)
by: Alvarez, Luis E., et al.
Published: (2024)
Reinforcement Learning with $ω$-Regular Objectives and Constraints
by: Wagner, Dominik, et al.
Published: (2025)
by: Wagner, Dominik, et al.
Published: (2025)
How Ensembles of Distilled Policies Improve Generalisation in Reinforcement Learning
by: Weltevrede, Max, et al.
Published: (2025)
by: Weltevrede, Max, et al.
Published: (2025)
Value Bonuses using Ensemble Errors for Exploration in Reinforcement Learning
by: Wahab, Abdul, et al.
Published: (2026)
by: Wahab, Abdul, et al.
Published: (2026)
$β$-GNN: A Robust Ensemble Approach Against Graph Structure Perturbation
by: Aslan, Haci Ismail, et al.
Published: (2025)
by: Aslan, Haci Ismail, et al.
Published: (2025)
Multi-level Certified Defense Against Poisoning Attacks in Offline Reinforcement Learning
by: Liu, Shijie, et al.
Published: (2025)
by: Liu, Shijie, et al.
Published: (2025)
Prototype Guided Backdoor Defense
by: Amula, Venkat Adithya, et al.
Published: (2025)
by: Amula, Venkat Adithya, et al.
Published: (2025)
Ensemble Successor Representations for Task Generalization in Offline-to-Online Reinforcement Learning
by: Wang, Changhong, et al.
Published: (2024)
by: Wang, Changhong, et al.
Published: (2024)
FORLER: Federated Offline Reinforcement Learning with Q-Ensemble and Actor Rectification
by: Qiao, Nan, et al.
Published: (2026)
by: Qiao, Nan, et al.
Published: (2026)
SB-TRPO: Towards Safe Reinforcement Learning with Hard Constraints
by: Wagner, Dominik, et al.
Published: (2025)
by: Wagner, Dominik, et al.
Published: (2025)
Large Language Model-Based Reward Design for Deep Reinforcement Learning-Driven Autonomous Cyber Defense
by: Mukherjee, Sayak, et al.
Published: (2025)
by: Mukherjee, Sayak, et al.
Published: (2025)
The Disparate Benefits of Deep Ensembles
by: Schweighofer, Kajetan, et al.
Published: (2024)
by: Schweighofer, Kajetan, et al.
Published: (2024)
An Invitation to Deep Reinforcement Learning
by: Jaeger, Bernhard, et al.
Published: (2023)
by: Jaeger, Bernhard, et al.
Published: (2023)
A Unified Deep Reinforcement Learning Approach for Close Enough Traveling Salesman Problem
by: Fan, Mingfeng, et al.
Published: (2025)
by: Fan, Mingfeng, et al.
Published: (2025)
An End-to-End Deep Reinforcement Learning Approach for Solving the Traveling Salesman Problem with Drones
by: Zeng, Taihelong, et al.
Published: (2025)
by: Zeng, Taihelong, et al.
Published: (2025)
Similar Items
-
Learning Expressive Priors for Generalization and Uncertainty Estimation in Neural Networks
by: Schnaus, Dominik, et al.
Published: (2023) -
DrivIng: A Large-Scale Multimodal Driving Dataset with Full Digital Twin Integration
by: Rößle, Dominik, et al.
Published: (2026) -
Enhancing Robustness in Deep Reinforcement Learning: A Lyapunov Exponent Approach
by: Young, Rory, et al.
Published: (2024) -
Structure in Deep Reinforcement Learning: A Survey and Open Problems
by: Mohan, Aditya, et al.
Published: (2023) -
UACER: An Uncertainty-Adaptive Critic Ensemble Framework for Robust Adversarial Reinforcement Learning
by: Wu, Jiaxi, et al.
Published: (2025)