Probabilistic Verification of Recurrent Neural Networks for Single and Multi-Agent Reinforcement Learning
Fuente:
arXiv
Saved in:
| Main Authors: | Marzari, Luca, Marchesini, Enrico |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Designing Control Barrier Function via Probabilistic Enumeration for Safe Reinforcement Learning Navigation
by: Marzari, Luca, et al.
Published: (2025)
by: Marzari, Luca, et al.
Published: (2025)
Enumerating Safe Regions in Deep Neural Networks with Provable Probabilistic Guarantees
by: Marzari, Luca, et al.
Published: (2023)
by: Marzari, Luca, et al.
Published: (2023)
Probabilistically Tightened Linear Relaxation-based Perturbation Analysis for Neural Network Verification
by: Marzari, Luca, et al.
Published: (2025)
by: Marzari, Luca, et al.
Published: (2025)
On Stateful Value Factorization in Multi-Agent Reinforcement Learning
by: Marchesini, Enrico, et al.
Published: (2024)
by: Marchesini, Enrico, et al.
Published: (2024)
Advancing Neural Network Verification through Hierarchical Safety Abstract Interpretation
by: Marzari, Luca, et al.
Published: (2025)
by: Marzari, Luca, et al.
Published: (2025)
Improving Policy Optimization via $\varepsilon$-Retrain
by: Marzari, Luca, et al.
Published: (2024)
by: Marzari, Luca, et al.
Published: (2024)
On the Probabilistic Learnability of Compact Neural Network Preimage Bounds
by: Marzari, Luca, et al.
Published: (2025)
by: Marzari, Luca, et al.
Published: (2025)
Rigorous Probabilistic Guarantees for Robust Counterfactual Explanations
by: Marzari, Luca, et al.
Published: (2024)
by: Marzari, Luca, et al.
Published: (2024)
Probabilistic Verification of Neural Networks via Efficient Probabilistic Hull Generation
by: Li, Jingyang, et al.
Published: (2026)
by: Li, Jingyang, et al.
Published: (2026)
Macro-Action Based Multi-Agent Instruction Following through Value Cancellation
by: Lin, Wo Wei, et al.
Published: (2026)
by: Lin, Wo Wei, et al.
Published: (2026)
Probabilistic Multi-Regional Solar Power Forecasting with Any-Quantile Recurrent Neural Networks
by: Smyl, Slawek, et al.
Published: (2026)
by: Smyl, Slawek, et al.
Published: (2026)
Solving Probabilistic Verification Problems of Neural Networks using Branch and Bound
by: Boetius, David, et al.
Published: (2024)
by: Boetius, David, et al.
Published: (2024)
SAVER: A Toolbox for Sampling-Based, Probabilistic Verification of Neural Networks
by: Sivaramakrishnan, Vignesh, et al.
Published: (2024)
by: Sivaramakrishnan, Vignesh, et al.
Published: (2024)
Probabilistic Modeling of Spiking Neural Networks with Contract-Based Verification
by: Yao, Zhen, et al.
Published: (2025)
by: Yao, Zhen, et al.
Published: (2025)
Towards Generalizability of Multi-Agent Reinforcement Learning in Graphs with Recurrent Message Passing
by: Weil, Jannis, et al.
Published: (2024)
by: Weil, Jannis, et al.
Published: (2024)
BaB-prob: Branch and Bound with Preactivation Splitting for Probabilistic Verification of Neural Networks
by: Wang, Fangji, et al.
Published: (2025)
by: Wang, Fangji, et al.
Published: (2025)
Think Smart, Act SMARL! Analyzing Probabilistic Logic Shields for Multi-Agent Reinforcement Learning
by: Chatterji, Satchit, et al.
Published: (2024)
by: Chatterji, Satchit, et al.
Published: (2024)
Graph Neural Networks, Deep Reinforcement Learning and Probabilistic Topic Modeling for Strategic Multiagent Settings
by: Chalkiadakis, Georgios, et al.
Published: (2025)
by: Chalkiadakis, Georgios, et al.
Published: (2025)
Probabilistic Performance Guarantees for Multi-Task Reinforcement Learning
by: Schnitzer, Yannik, et al.
Published: (2026)
by: Schnitzer, Yannik, et al.
Published: (2026)
NeuroMAS: Multi-Agent Systems as Neural Networks with Joint Reinforcement Learning
by: Lu, Haoran, et al.
Published: (2026)
by: Lu, Haoran, et al.
Published: (2026)
Recurrent Neural Network on PICTURE Model
by: Xu, Weihan
Published: (2024)
by: Xu, Weihan
Published: (2024)
Novel Multi-Agent Action Masked Deep Reinforcement Learning for General Industrial Assembly Lines Balancing Problems
by: Ali, Ali Mohamed, et al.
Published: (2025)
by: Ali, Ali Mohamed, et al.
Published: (2025)
NaviGNN: Multi-Agent Reinforcement Learning and Graph Neural Network for Sustainable Mobility in Futuristic Smart Cities
by: Bahi, Abderaouf, et al.
Published: (2025)
by: Bahi, Abderaouf, et al.
Published: (2025)
A Survey of Multi-Agent Deep Reinforcement Learning with Graph Neural Network-Based Communication
by: Cuzin-Rambaud, Valentin, et al.
Published: (2026)
by: Cuzin-Rambaud, Valentin, et al.
Published: (2026)
Recurrent Reinforcement Learning with Memoroids
by: Morad, Steven, et al.
Published: (2024)
by: Morad, Steven, et al.
Published: (2024)
Concept Learning for Cooperative Multi-Agent Reinforcement Learning
by: Ge, Zhonghan, et al.
Published: (2025)
by: Ge, Zhonghan, et al.
Published: (2025)
On Centralized Critics in Multi-Agent Reinforcement Learning
by: Lyu, Xueguang, et al.
Published: (2024)
by: Lyu, Xueguang, et al.
Published: (2024)
Formal Ethical Obligations in Reinforcement Learning Agents: Verification and Policy Updates
by: Shea-Blymyer, Colin, et al.
Published: (2024)
by: Shea-Blymyer, Colin, et al.
Published: (2024)
Multi-Agent Reinforcement Learning for Energy Networks: Computational Challenges, Progress and Open Problems
by: Keren, Sarah, et al.
Published: (2024)
by: Keren, Sarah, et al.
Published: (2024)
RL2Grid: Benchmarking Reinforcement Learning in Power Grid Operations
by: Marchesini, Enrico, et al.
Published: (2025)
by: Marchesini, Enrico, et al.
Published: (2025)
Neural Network Verification using Partial Multi-Neuron Relaxation
by: Shmuel, Ido, et al.
Published: (2026)
by: Shmuel, Ido, et al.
Published: (2026)
Single Agent Robust Deep Reinforcement Learning for Bus Fleet Control
by: Zhang, Yifan
Published: (2025)
by: Zhang, Yifan
Published: (2025)
Incremental Neural Network Verification via Learned Conflicts
by: Elsaleh, Raya, et al.
Published: (2026)
by: Elsaleh, Raya, et al.
Published: (2026)
Adaptive Robust Estimator for Multi-Agent Reinforcement Learning
by: Li, Zhongyi, et al.
Published: (2026)
by: Li, Zhongyi, et al.
Published: (2026)
Coordination Graphs for Constrained Multi-Agent Reinforcement Learning
by: Amaya-Corredor, Santiago, et al.
Published: (2026)
by: Amaya-Corredor, Santiago, et al.
Published: (2026)
Reinforcement Networks: novel framework for collaborative Multi-Agent Reinforcement Learning tasks
by: Kryzhanovskiy, Maksim, et al.
Published: (2025)
by: Kryzhanovskiy, Maksim, et al.
Published: (2025)
Robust and Efficient Communication in Multi-Agent Reinforcement Learning
by: Liu, Zejiao, et al.
Published: (2025)
by: Liu, Zejiao, et al.
Published: (2025)
Explaining Decentralized Multi-Agent Reinforcement Learning Policies
by: Boggess, Kayla, et al.
Published: (2025)
by: Boggess, Kayla, et al.
Published: (2025)
Heterogeneity in Multi-Agent Reinforcement Learning
by: Hu, Tianyi, et al.
Published: (2025)
by: Hu, Tianyi, et al.
Published: (2025)
MASH: Cooperative-Heterogeneous Multi-Agent Reinforcement Learning for Single Humanoid Robot Locomotion
by: Liu, Qi, et al.
Published: (2025)
by: Liu, Qi, et al.
Published: (2025)
Similar Items
-
Designing Control Barrier Function via Probabilistic Enumeration for Safe Reinforcement Learning Navigation
by: Marzari, Luca, et al.
Published: (2025) -
Enumerating Safe Regions in Deep Neural Networks with Provable Probabilistic Guarantees
by: Marzari, Luca, et al.
Published: (2023) -
Probabilistically Tightened Linear Relaxation-based Perturbation Analysis for Neural Network Verification
by: Marzari, Luca, et al.
Published: (2025) -
On Stateful Value Factorization in Multi-Agent Reinforcement Learning
by: Marchesini, Enrico, et al.
Published: (2024) -
Advancing Neural Network Verification through Hierarchical Safety Abstract Interpretation
by: Marzari, Luca, et al.
Published: (2025)