Copertina

Continual Adversarial Reinforcement Learning (CARL) of False Data Injection detection: forgetting and explainability

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Aslami, Pooja, Chen, Kejun, Hansen, Timothy M., Hassanaly, Malik
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Machine Learning Artificial Intelligence
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Discovery of False Data Injection Schemes on Frequency Controllers with Reinforcement Learning
di: Prasad, Romesh, et al.
Pubblicazione: (2024)

Detection of False Data Injection Attacks (FDIA) on Power Dynamical Systems With a State Prediction Method
di: Sahu, Abhijeet, et al.
Pubblicazione: (2024)

Adversarial Multi-Agent Reinforcement Learning for Proactive False Data Injection Detection
di: Chen, Kejun, et al.
Pubblicazione: (2024)

Multi-Agent Reinforcement Learning for Assessing False-Data Injection Attacks on Transportation Networks
di: Eghtesad, Taha, et al.
Pubblicazione: (2023)

Swift Hydra: Self-Reinforcing Generative Framework for Anomaly Detection with Multiple Mamba Models
di: Do, Nguyen, et al.
Pubblicazione: (2025)

CARL: Criticality-Aware Agentic Reinforcement Learning
di: Shen, Leyang, et al.
Pubblicazione: (2025)

False Data Injection Attack Detection in Edge-based Smart Metering Networks with Federated Learning
di: Uddin, Md Raihan, et al.
Pubblicazione: (2024)

Learning to Inject: Automated Prompt Injection via Reinforcement Learning
di: Chen, Xin, et al.
Pubblicazione: (2026)

Scale-free Adversarial Reinforcement Learning
di: Chen, Mingyu, et al.
Pubblicazione: (2024)

Preserving Plasticity in Continual Learning with Adaptive Linearity Injection
di: Rohani, Seyed Roozbeh Razavi, et al.
Pubblicazione: (2025)

GenAI-FDIA: Physics-Informed Generative Models for False Data Injection Attacks
di: Razzaque, Mohammad A., et al.
Pubblicazione: (2026)

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor
di: Ji, Han, et al.
Pubblicazione: (2025)

Hierarchical Reinforcement Learning with Runtime Safety Shielding for Power Grid Operation
di: Malik, Gitesh
Pubblicazione: (2026)

Model-Based Offline Reinforcement Learning with Adversarial Data Augmentation
di: Cao, Hongye, et al.
Pubblicazione: (2025)

Reinforcement Learning with Euclidean Data Augmentation for State-Based Continuous Control
di: Luo, Jinzhu, et al.
Pubblicazione: (2024)

Offline Reinforcement Learning with Penalized Action Noise Injection
di: Oh, JunHyeok, et al.
Pubblicazione: (2025)

Behavior Injection: Preparing Language Models for Reinforcement Learning
di: Cen, Zhepeng, et al.
Pubblicazione: (2025)

Adversarial Diffusion for Robust Reinforcement Learning
di: Foffano, Daniele, et al.
Pubblicazione: (2025)

Adversarial Reinforcement Learning for Detecting False Data Injection Attacks in Vehicular Routing
di: Eghtesad, Taha, et al.
Pubblicazione: (2026)

Maintaining Adversarial Robustness in Continuous Learning
di: Ru, Xiaolei, et al.
Pubblicazione: (2024)

Regret-Based Defense in Adversarial Reinforcement Learning
di: Belaire, Roman, et al.
Pubblicazione: (2023)

Data-Driven Lipschitz Continuity: A Cost-Effective Approach to Improve Adversarial Robustness
di: Chen, Erh-Chung, et al.
Pubblicazione: (2024)

Practical Adversarial Attacks on Stochastic Bandits via Fake Data Injection
di: Zeng, Qirun, et al.
Pubblicazione: (2025)

Soup to go: mitigating forgetting during continual learning with model averaging
di: Kleiman, Anat, et al.
Pubblicazione: (2025)

Causal-Aware Generative Adversarial Networks with Reinforcement Learning
di: Nguyen, Tu Anh Hoang, et al.
Pubblicazione: (2025)

Diffusion Guided Adversarial State Perturbations in Reinforcement Learning
di: Sun, Xiaolin, et al.
Pubblicazione: (2025)

Adversarial Reinforcement Learning Framework for ESP Cheater Simulation
di: Park, Inkyu, et al.
Pubblicazione: (2025)

Rethinking Adversarial Attacks in Reinforcement Learning from Policy Distribution Perspective
di: Duan, Tianyang, et al.
Pubblicazione: (2025)

On the Implicit Adversariality of Catastrophic Forgetting in Deep Continual Learning
di: Peng, Ze, et al.
Pubblicazione: (2025)

Mitigating Adversarial Perturbations for Deep Reinforcement Learning via Vector Quantization
di: Luu, Tung M., et al.
Pubblicazione: (2024)

Solving Continual Offline Reinforcement Learning with Decision Transformer
di: Huang, Kaixin, et al.
Pubblicazione: (2024)

Continual Learning as Computationally Constrained Reinforcement Learning
di: Kumar, Saurabh, et al.
Pubblicazione: (2023)

An explainable approach to detect case law on housing and eviction issues within the HUDOC database
di: Mohammadi, Mohammad, et al.
Pubblicazione: (2024)

Robust Deep Reinforcement Learning against Adversarial Behavior Manipulation
di: Yamabe, Shojiro, et al.
Pubblicazione: (2024)

Robust Model-Based Reinforcement Learning with an Adversarial Auxiliary Model
di: Herremans, Siemen, et al.
Pubblicazione: (2024)

GAR: Generative Adversarial Reinforcement Learning for Formal Theorem Proving
di: Wang, Ruida, et al.
Pubblicazione: (2025)

Adversarial Policy Optimization for Offline Preference-based Reinforcement Learning
di: Kang, Hyungkyu, et al.
Pubblicazione: (2025)

Parseval Regularization for Continual Reinforcement Learning
di: Chung, Wesley, et al.
Pubblicazione: (2024)

Rethinking the Foundations for Continual Reinforcement Learning
di: Elelimy, Esraa, et al.
Pubblicazione: (2025)

A Survey of Continual Reinforcement Learning
di: Pan, Chaofan, et al.
Pubblicazione: (2025)