Robust Deep Reinforcement Learning with Adversarial Attacks
Not on the map. Why?
Cited by 45 in Deep reinforcement learning methods, but placed by its own abstract, which didn’t fit.
Abstract (arXiv)
This paper proposes adversarial attacks for Reinforcement Learning (RL) and then improves the robustness of Deep Reinforcement Learning algorithms (DRL) to parameter uncertainties with the help of these attacks. We show that even a naively engineered attack successfully degrades the performance of DRL algorithm. We further improve the attack using gradient information of an engineered loss function which leads to further degradation in performance. These attacks are then leveraged during training to improve the robustness of RL within robust control framework. We show that this adversarial training of DRL algorithms like Deep Double Q learning and Deep Deterministic Policy Gradients leads to significant increase in robustness to parameter variations for RL benchmarks such as Cart-pole, Mountain Car, Hopper and Half Cheetah environment.
Key facts. Cited by 154 papers in the map (data through 14 Oct 2026). First posted on arXiv 11 Dec 2017.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2021: 34; 2022: 29; 2023: 27; 2024: 25; 2025: 28; 2026: 11.
154 papers.
Sort:
By area:
- 2021Recent Advances in Adversarial Training for Adversarial Robustnesscited by 279
- 2021Beta-CROWN: Efficient Bound Propagation with Per-neuron Split Constraints for Complete and Incomplete Neural Network Robustness Verificationcited by 228
- 2021Robust Reinforcement Learning on State Observations with Learned Optimal Adversarycited by 135
- 2021Recurrent Model-Free RL Can Be a Strong Baseline for Many POMDPscited by 122
- 2022RAMBO-RL: Robust Adversarial Model-Based Offline Reinforcement Learningcited by 115
- 2022A Survey of Multi-Agent Deep Reinforcement Learning with Communicationcited by 104
- 2021Online Robust Reinforcement Learning with Model Uncertaintycited by 96
- 2022RORL: Robust Offline Reinforcement Learning via Conservative Smoothingcited by 84
- 2022Policy Gradient Method For Robust Reinforcement Learningcited by 69
- 2021Who Is the Strongest Enemy? Towards Optimal and Efficient Evasion Attacks in Deep RLcited by 55
- 2023Double Pessimism is Provably Efficient for Distributionally Robust Offline Reinforcement Learning: Generic Algorithm and Robust Partial Coveragecited by 51
- 2021Reinforcement Learning for Selective Key Applications in Power Systems: Recent Advances and Future Challengescited by 50
38 more
- 2022Sound Adversarial Audio-Visual Navigationcited by 48
- 2022Efficient Adversarial Training without Attacking: Worst-Case-Aware Robust Reinforcement Learningcited by 43
- 2021CROP: Certifying Robust Policies for Reinforcement Learning through Functional Smoothingcited by 42
- 2021Policy Smoothing for Provably Robust Reinforcement Learningcited by 40
- 2022On the Robustness of Safe Reinforcement Learning under Observational Perturbationscited by 38
- 2022Trustworthy Reinforcement Learning Against Intrinsic Vulnerabilities: Robustness, Safety, and Generalizabilitycited by 36
- 2022Distributionally Robust Offline Reinforcement Learning with Linear Function Approximationcited by 32
- 2022COPA: Certifying Robust Policies for Offline Reinforcement Learning against Poisoning Attackscited by 26
- 2021Evaluating the Robustness of Collaborative Agentscited by 25
- 2022What is the Solution for State-Adversarial Multi-Agent Reinforcement Learning?cited by 22
- 2023Robust Average-Reward Markov Decision Processescited by 22
- 2023Adversarial Robust Deep Reinforcement Learning Requires Redefining Robustnesscited by 19
- 2021Center Smoothing: Certified Robustness for Networks with Structured Outputscited by 18
- 2024Minimax Optimal and Computationally Efficient Algorithms for Distributionally Robust Offline Reinforcement Learningcited by 18
- 2024Diffusion Policy Attacker: Crafting Adversarial Attacks for Diffusion-based Policiescited by 18
- 2021Optimistic Policy Optimization is Provably Efficient in Non-stationary MDPscited by 16
- 2024RAT: Adversarial Attacks on Deep Reinforcement Agents for Targeted Behaviorscited by 16
- 2021RLOps: Development Life-cycle of Reinforcement Learning Aided Open RANcited by 15
- 2022Robust Deep Reinforcement Learning through Bootstrapped Opportunistic Curriculumcited by 15
- 2022Robust Constrained Reinforcement Learningcited by 15
- 2023Robust multi-agent coordination via evolutionary generation of auxiliary adversarial attackerscited by 15
- 2023Implicit Poisoning Attacks in Two-Agent Reinforcement Learning: Adversarial Policies for Training-Time Attackscited by 14
- 2024Rethinking Robustness Assessment: Adversarial Attacks on Learning-based Quadrupedal Locomotion Controllerscited by 14
- 2021Multi-Task Federated Reinforcement Learning with Adversariescited by 13
- 2021Understanding Adversarial Attacks on Observations in Deep Reinforcement Learningcited by 13
- 2021Targeted Attack on Deep RL-based Autonomous Driving with Learned Visual Patternscited by 13
- 2022A Search-Based Testing Approach for Deep Reinforcement Learning Agentscited by 13
- 2025Robust Gymnasium: A Unified Modular Benchmark for Robust Reinforcement Learningcited by 13
- 2021Exploring the Training Robustness of Distributional Reinforcement Learning against Noisy State Observationscited by 12
- 2021MDPFuzz: Testing Models Solving Markov Decision Processescited by 12
- 2021Deep Reinforcement Learning Policies Learn Shared Adversarial Features Across MDPscited by 12
- 2023ORL-AUDITOR: Dataset Auditing in Offline Deep Reinforcement Learningcited by 11
- 2021Resilient Machine Learning for Networked Cyber Physical Systems: A Survey for Machine Learning Security to Securing Machine Learning for CPScited by 10
- 2023SMARLA: A Safety Monitoring Approach for Deep Reinforcement Learning Agentscited by 10
- 2023Adjustable Robust Reinforcement Learning for Online 3D Bin Packingcited by 10
- 2025Rethinking Adversarial Attacks in Reinforcement Learning from Policy Distribution Perspectivecited by 10
- 2022Provable Sim-to-real Transfer in Continuous Domain with Partial Observationscited by 9
- 2023Decision-Making Under Uncertainty: Beyond Probabilitiescited by 9
50 most cited of 154 All 154 (JSON)
- 2026Admissable: Training Reinforcement Learning Agents against Adversarial Missingness14 Sep 2026
- 2026Robust Policy Optimization via Adversarial Importance Sampling11 Sep 2026
- 2026CIVA: Critic-Induced Value-Subspace Attacks on Visual World-Model Agents21 Aug 2026
- 2026Off the Rails: Hijacking the Scoring Head in Generative End-to-End Driving Planners with Safety-Violating Adversarial Perturbations29 Jun 2026
- 2026RoAd-RL: A Unified Library and Benchmark for Robust Adversarial Reinforcement Learning29 Jun 2026
- 2026Interaction-Breaking Adversarial Learning Framework for Robust Multi-Agent Reinforcement Learning18 May 2026
- 2026Finding the Weakest Link: Adversarial Attack against Multi-Agent Communications13 May 2026
- 2026Efficient Preference Poisoning Attack on Offline RLHF4 May 2026
- 2026Advantage-based Temporal Attack in Reinforcement Learning23 Feb 2026
- 2026Reinforcement Learning for Control Systems with Time Delays: A Comprehensive Survey30 Jan 2026
- 2026Bayesian Robust Financial Trading with Adversarial Synthetic Market Data14 Jan 2026
- 2025Online Robust Reinforcement Learning with General Function Approximation22 Dec 2025
38 more
- 2025On the Tension Between Optimality and Adversarial Robustness in Policy Optimization1 Dec 2025
- 2025Adversarial Reinforcement Learning for Robust Control of Fixed-Wing Aircraft under Model Uncertainty18 Oct 2025
- 2025Provably Invincible Adversarial Attacks on Reinforcement Learning Systems: A Rate-Distortion Information-Theoretic Approach15 Oct 2025
- 2025ADARL: Adaptive Low-Rank Structures for Robust Policy Learning under Uncertainty13 Oct 2025
- 2025Empirical Study on Robustness and Resilience in Cooperative Multi-Agent Reinforcement Learning13 Oct 2025
- 2025Neutral Agent-based Adversarial Policy Learning against Deep Reinforcement Learning in Multi-party Open Systems13 Oct 2025
- 2025SPiDR: A Simple Approach for Zero-Shot Safety in Sim-to-Real Transfer23 Sep 2025
- 2025Temporal Logic-Based Multi-Vehicle Backdoor Attacks against Offline RL Agents in End-to-end Autonomous Driving21 Sep 2025
- 2025Distributed Detection of Adversarial Attacks in Multi-Agent Reinforcement Learning with Continuous Action Space21 Aug 2025
- 2025ORVIT: Near-Optimal Online Distributionally Robust Reinforcement Learning5 Aug 2025
- 2025Advancing Robustness in Deep Reinforcement Learning with an Ensemble Defense Approach22 Jul 2025
- 2025LyAm: Robust Non-Convex Optimization for Stable Learning in Noisy Environments15 Jul 2025
- 2025Beyond Training-time Poisoning: Component-level and Post-training Backdoors in Deep Reinforcement Learning7 Jul 2025
- 2025ARMOR: Robust Reinforcement Learning-based Control for UAVs under Physical Attacks27 Jun 2025
- 2025Meta Policy Switching for Secure UAV Deconfliction in Adversarial Airspace26 Jun 2025
- 2025Off-Policy Actor-Critic for Adversarial Observation Robustness: Virtual Alternative Training via Symmetric Policy Evaluation20 Jun 2025
- 2025Towards Robust Deep Reinforcement Learning against Environmental State Perturbation10 Jun 2025
- 2025Robust In-Context Reinforcement Learning Under Reward Poisoning Attacks7 Jun 2025
- 2025Backdoors in DRL: Four Environments Focusing on In-distribution Triggers22 May 2025
- 2025Neural Fidelity Calibration for Informative Sim-to-Real Adaptation11 Apr 2025
- 2025Robust Deep Reinforcement Learning in Robotics via Adaptive Gradient-Masked Adversarial Attacks26 Mar 2025
- 2025State-Aware Perturbation Optimization for Robust Deep Reinforcement Learning26 Mar 2025
- 2025Robust Gymnasium: A Unified Modular Benchmark for Robust Reinforcement Learning27 Feb 2025
- 2025How Vulnerable Is My Learned Policy? Universal Adversarial Perturbation Attacks On Modern Behavior Cloning Policies6 Feb 2025
- 2025Wolfpack Adversarial Attack for Robust Multi-Agent Reinforcement Learning5 Feb 2025
- 2025CAMP in the Odyssey: Provably Robust Reinforcement Learning with Certified Radius Maximization29 Jan 2025
- 2025Rethinking Adversarial Attacks in Reinforcement Learning from Policy Distribution Perspective7 Jan 2025
- 2024RAT: Adversarial Attacks on Deep Reinforcement Agents for Targeted Behaviors14 Dec 2024
- 2024Optimizing Sensor Redundancy in Sequential Decision-Making Problems10 Dec 2024
- 2024Constrained Optimal Fuel Consumption of HEVs under Observational Noise28 Oct 2024
- 2024DyPNIPP: Predicting Environment Dynamics for RL-based Robust Informative Path Planning22 Oct 2024
- 2024Mitigating Adversarial Perturbations for Deep Reinforcement Learning via Vector Quantization4 Oct 2024
- 2024Robust off-policy Reinforcement Learning via Soft Constrained Adversary31 Aug 2024
- 2024SpecGuard: Specification Aware Recovery for Robotic Autonomous Vehicles from Physical Attacks27 Aug 2024
- 2024Training Verifiably Robust Agents Using Set-Based Reinforcement Learning17 Aug 2024
- 2024On the Perturbed States for Transformed Input-robust Reinforcement Learning31 Jul 2024
- 2024Breaking the Barrier: Enhanced Utility and Robustness in Smoothed DRL Agents26 Jun 2024
- 2024On Minimizing Adversarial Counterfactual Error in Adversarial RL7 Jun 2024
50 newest of 154 All 154 (JSON)
- 2024RAT: Adversarial Attacks on Deep Reinforcement Agents for Targeted Behaviorscited by 16
- 2024Rethinking Robustness Assessment: Adversarial Attacks on Learning-based Quadrupedal Locomotion Controllerscited by 14
- 2025Robust Gymnasium: A Unified Modular Benchmark for Robust Reinforcement Learningcited by 13
- 2025Rethinking Adversarial Attacks in Reinforcement Learning from Policy Distribution Perspectivecited by 10
- 2024Beyond Worst-case Attacks: Robust RL with Adaptive Defense via Non-dominated Policiescited by 8
- 2025State-Aware Perturbation Optimization for Robust Deep Reinforcement Learningcited by 8
- 2025SPiDR: A Simple Approach for Zero-Shot Safety in Sim-to-Real Transfercited by 8
- 2024Assessing the Impact of Distribution Shift on Reinforcement Learning Performancecited by 7
- 2025Robust Deep Reinforcement Learning in Robotics via Adaptive Gradient-Masked Adversarial Attackscited by 7
- 2024Mitigating Adversarial Perturbations for Deep Reinforcement Learning via Vector Quantizationcited by 6
- 2025ORVIT: Near-Optimal Online Distributionally Robust Reinforcement Learningcited by 6
- 2024Towards Optimal Adversarial Robust Q-learning with Bellman Infinity-errorcited by 4
12 most cited of 43 All 43 (JSON)
- 2026Admissable: Training Reinforcement Learning Agents against Adversarial Missingness14 Sep 2026
- 2026Robust Policy Optimization via Adversarial Importance Sampling11 Sep 2026
- 2026RoAd-RL: A Unified Library and Benchmark for Robust Adversarial Reinforcement Learning29 Jun 2026
- 2026Advantage-based Temporal Attack in Reinforcement Learning23 Feb 2026
- 2026Reinforcement Learning for Control Systems with Time Delays: A Comprehensive Survey30 Jan 2026
- 2025Online Robust Reinforcement Learning with General Function Approximation22 Dec 2025
- 2025On the Tension Between Optimality and Adversarial Robustness in Policy Optimization1 Dec 2025
- 2025Adversarial Reinforcement Learning for Robust Control of Fixed-Wing Aircraft under Model Uncertainty18 Oct 2025
- 2025Provably Invincible Adversarial Attacks on Reinforcement Learning Systems: A Rate-Distortion Information-Theoretic Approach15 Oct 2025
- 2025ADARL: Adaptive Low-Rank Structures for Robust Policy Learning under Uncertainty13 Oct 2025
- 2025Neutral Agent-based Adversarial Policy Learning against Deep Reinforcement Learning in Multi-party Open Systems13 Oct 2025
- 2025SPiDR: A Simple Approach for Zero-Shot Safety in Sim-to-Real Transfer23 Sep 2025
12 newest of 43 All 43 (JSON)
- 2022RAMBO-RL: Robust Adversarial Model-Based Offline Reinforcement Learningcited by 115
- 2022RORL: Robust Offline Reinforcement Learning via Conservative Smoothingcited by 84
- 2023Double Pessimism is Provably Efficient for Distributionally Robust Offline Reinforcement Learning: Generic Algorithm and Robust Partial Coveragecited by 51
- 2022Distributionally Robust Offline Reinforcement Learning with Linear Function Approximationcited by 32
- 2022COPA: Certifying Robust Policies for Offline Reinforcement Learning against Poisoning Attackscited by 26
- 2024Minimax Optimal and Computationally Efficient Algorithms for Distributionally Robust Offline Reinforcement Learningcited by 18
- 2023ORL-AUDITOR: Dataset Auditing in Offline Deep Reinforcement Learningcited by 11
- 2023MICRO: Model-Based Offline Reinforcement Learning with a Conservative Bellman Operatorcited by 9
- 2024Towards Robust Policy: Enhancing Offline Reinforcement Learning with Adversarial Attacks and Defensescited by 7
- 2025How Vulnerable Is My Learned Policy? Universal Adversarial Perturbation Attacks On Modern Behavior Cloning Policiescited by 3
- 2025How Vulnerable Is My Learned Policy? Universal Adversarial Perturbation Attacks On Modern Behavior Cloning Policies6 Feb 2025
- 2024Towards Robust Policy: Enhancing Offline Reinforcement Learning with Adversarial Attacks and Defenses18 May 2024
- 2024Minimax Optimal and Computationally Efficient Algorithms for Distributionally Robust Offline Reinforcement Learning14 Mar 2024
- 2023MICRO: Model-Based Offline Reinforcement Learning with a Conservative Bellman Operator7 Dec 2023
- 2023ORL-AUDITOR: Dataset Auditing in Offline Deep Reinforcement Learning6 Sep 2023
- 2023Double Pessimism is Provably Efficient for Distributionally Robust Offline Reinforcement Learning: Generic Algorithm and Robust Partial Coverage16 May 2023
- 2022Distributionally Robust Offline Reinforcement Learning with Linear Function Approximation14 Sep 2022
- 2022RORL: Robust Offline Reinforcement Learning via Conservative Smoothing6 Jun 2022
- 2022RAMBO-RL: Robust Adversarial Model-Based Offline Reinforcement Learning26 Apr 2022
- 2022COPA: Certifying Robust Policies for Offline Reinforcement Learning against Poisoning Attacks16 Mar 2022
- 2021Targeted Attack on Deep RL-based Autonomous Driving with Learned Visual Patternscited by 13
- 2021ARC: Adversarially Robust Control Policies for Autonomous Vehiclescited by 3
- 2022Security of Deep Reinforcement Learning for Autonomous Driving: A Surveycited by 2
- 2024SpecGuard: Specification Aware Recovery for Robotic Autonomous Vehicles from Physical Attackscited by 2
- 2026Off the Rails: Hijacking the Scoring Head in Generative End-to-End Driving Planners with Safety-Violating Adversarial Perturbationscited by 0
- 2026Off the Rails: Hijacking the Scoring Head in Generative End-to-End Driving Planners with Safety-Violating Adversarial Perturbations29 Jun 2026
- 2024SpecGuard: Specification Aware Recovery for Robotic Autonomous Vehicles from Physical Attacks27 Aug 2024
- 2022Security of Deep Reinforcement Learning for Autonomous Driving: A Survey12 Dec 2022
- 2021Targeted Attack on Deep RL-based Autonomous Driving with Learned Visual Patterns16 Sep 2021
- 2021ARC: Adversarially Robust Control Policies for Autonomous Vehicles9 Jul 2021
- 2021Recent Advances in Adversarial Training for Adversarial Robustnesscited by 279
- 2021Beta-CROWN: Efficient Bound Propagation with Per-neuron Split Constraints for Complete and Incomplete Neural Network Robustness Verificationcited by 228
- 2021Robust Reinforcement Learning on State Observations with Learned Optimal Adversarycited by 135
- 2021Recurrent Model-Free RL Can Be a Strong Baseline for Many POMDPscited by 122
- 2022A Survey of Multi-Agent Deep Reinforcement Learning with Communicationcited by 104
- 2021Online Robust Reinforcement Learning with Model Uncertaintycited by 96
- 2022Policy Gradient Method For Robust Reinforcement Learningcited by 69
- 2021Who Is the Strongest Enemy? Towards Optimal and Efficient Evasion Attacks in Deep RLcited by 55
- 2021Reinforcement Learning for Selective Key Applications in Power Systems: Recent Advances and Future Challengescited by 50
- 2022Sound Adversarial Audio-Visual Navigationcited by 48
- 2022Efficient Adversarial Training without Attacking: Worst-Case-Aware Robust Reinforcement Learningcited by 43
- 2021CROP: Certifying Robust Policies for Reinforcement Learning through Functional Smoothingcited by 42
12 most cited of 89 All 89 (JSON)
- 2026Interaction-Breaking Adversarial Learning Framework for Robust Multi-Agent Reinforcement Learning18 May 2026
- 2026Finding the Weakest Link: Adversarial Attack against Multi-Agent Communications13 May 2026
- 2026Bayesian Robust Financial Trading with Adversarial Synthetic Market Data14 Jan 2026
- 2025Empirical Study on Robustness and Resilience in Cooperative Multi-Agent Reinforcement Learning13 Oct 2025
- 2025Distributed Detection of Adversarial Attacks in Multi-Agent Reinforcement Learning with Continuous Action Space21 Aug 2025
- 2025LyAm: Robust Non-Convex Optimization for Stable Learning in Noisy Environments15 Jul 2025
- 2025Wolfpack Adversarial Attack for Robust Multi-Agent Reinforcement Learning5 Feb 2025
- 2024Constrained Optimal Fuel Consumption of HEVs under Observational Noise28 Oct 2024
- 2024DyPNIPP: Predicting Environment Dynamics for RL-based Robust Informative Path Planning22 Oct 2024
- 2024A call for embodied AI6 Feb 2024
- 2023Robust Communicative Multi-Agent Reinforcement Learning with Active Defense16 Dec 2023
- 2023Improve Robustness of Reinforcement Learning against Observation Perturbations via l_∞ Lipschitz Policy Networks14 Dec 2023
12 newest of 89 All 89 (JSON)