Imagen de Portada

Reinforcement Learning Based Minimum State-flipped Control for the Reachability of Boolean Control Networks

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Ni, Jingjie, Tang, Yang, Li, Fangfei
Formato:	Preprint
Publicado:	2023
Materias:	Systems and Control
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Reinforcement Learning based Constrained Optimal Control: an Interpretable Reward Design
por: Ni, Jingjie, et al.
Publicado: (2025)

Reference Output Tracking in Boolean Control Networks
por: Disarò, Giorgia, et al.
Publicado: (2026)

On the Number of Control Nodes of Threshold and XOR Boolean Networks
por: Fok, Christopher H., et al.
Publicado: (2025)

Neural Network-assisted Interval Reachability for Systems with Control Barrier Function-Based Safe Controllers
por: Ajeyemi, Damola, et al.
Publicado: (2025)

Minimum observability of probabilistic Boolean networks
por: Xu, Jiayi, et al.
Publicado: (2024)

Reachability and Controllability Analysis of the State Covariance for Linear Stochastic Systems
por: Liu, Fengjiao, et al.
Publicado: (2024)

Learning Neural Network Safe Tracking Controllers from Backward Reachable Sets
por: Xu, Yuezhu, et al.
Publicado: (2025)

On the Number of Control Nodes in Boolean Networks with Degree Constraints
por: Sun, Liangjie, et al.
Publicado: (2025)

Secure Distributed Consensus Estimation under False Data Injection Attacks: A Defense Strategy Based on Partial Channel Coding
por: Huang, Jiahao, et al.
Publicado: (2025)

A Forward Reachability Perspective on Control Barrier Functions and Discount Factors in Reachability Analysis
por: Choi, Jason J., et al.
Publicado: (2023)

Koopman-Hopf Hamilton-Jacobi Reachability and Control
por: Sharpless, Will, et al.
Publicado: (2023)

Probabilistic Reachability Analysis of Stochastic Control Systems
por: Jafarpour, Saber, et al.
Publicado: (2024)

Submodular Multi-Agent Policy Learning for Online Distributed Task Allocation in Open Multi-Agent Systems
por: Liu, Jing, et al.
Publicado: (2026)

Unifying Hamilton-Jacobi Reachability and Reinforcement Learning
por: Solanki, Prashant, et al.
Publicado: (2026)

Parametric Reachable Sets Via Controlled Dynamical Embeddings
por: Harapanahalli, Akash, et al.
Publicado: (2025)

On the Reachability and Controllability of Temporal Continuous-Time Linear Networks: A Generic Analysis
por: Zhang, Yuan, et al.
Publicado: (2023)

Scalable Reinforcement Learning for Linear-Quadratic Control of Networks
por: Olsson, Johan, et al.
Publicado: (2024)

Finite-Sample-Based Reachability for Safe Control with Gaussian Process Dynamics
por: Prajapat, Manish, et al.
Publicado: (2025)

Contraction-Guided Adaptive Partitioning for Reachability Analysis of Neural Network Controlled Systems
por: Harapanahalli, Akash, et al.
Publicado: (2023)

Certifying Hamilton-Jacobi Reachability Learned via Reinforcement Learning
por: Solanki, Prashant, et al.
Publicado: (2026)

Bridging Model Predictive Control and Deep Learning for Scalable Reachability Analysis
por: Feng, Zeyuan, et al.
Publicado: (2025)

Reachable Sets-based Trajectory Planning Combining Reinforcement Learning and iLQR
por: Huang, Wenjie, et al.
Publicado: (2025)

Reinforcement Learning Based Robust Volt/Var Control in Active Distribution Networks With Imprecisely Known Delay
por: Cheng, Hong, et al.
Publicado: (2024)

Ignition Point Reachability for Aerodynamically-Controlled Reusable Launch Vehicles
por: Chung, Benjamin, et al.
Publicado: (2025)

Geometric Reachability for Attitude Control Systems via Contraction Theory
por: Xu, Chencheng, et al.
Publicado: (2025)

Privacy Preservation by Local Design in Cooperative Networked Control Systems
por: Yang, Chao, et al.
Publicado: (2022)

Robust Data-EnablEd Predictive Leading Cruise Control via Reachability Analysis
por: Li, Shuai, et al.
Publicado: (2024)

Safe Reinforcement Learning-Based Eco-Driving Control for Mixed Traffic Flows With Disturbances
por: Lu, Ke, et al.
Publicado: (2024)

Robust Nonlinear Data-Driven Predictive Control for Mixed Vehicle Platoons via Koopman Operator and Reachability Analysis
por: Li, Shuai, et al.
Publicado: (2025)

Control Synthesis for Multiple Reach-Avoid Tasks via Hamilton-Jacobi Reachability Analysis
por: Chen, Yu, et al.
Publicado: (2025)

Deep Reinforcement Learning-Based Control Strategy with Direct Gate Control for Buck Converters
por: Katayama, Noboru
Publicado: (2025)

Viscosity CBFs: Bridging the Control Barrier Function and Hamilton-Jacobi Reachability Frameworks in Safe Control Theory
por: Hirsch, Dylan, et al.
Publicado: (2025)

Parallel Differentiable Reachability for Learning and Planning with Certified Neural Dynamics and Controllers
por: Shen, Keyi, et al.
Publicado: (2026)

The Reachability Problem for Neural-Network Control Systems
por: Schilling, Christian, et al.
Publicado: (2024)

PRREACH: Probabilistic Risk Assessment Using Reachability for UAV Control
por: Fronda, Nicole, et al.
Publicado: (2025)

Minimum Reachability Probabilities in Rectangular Automata with Random Clocks
por: Delicaris, Joanna, et al.
Publicado: (2026)

A Holistic Power Optimization Approach for Microgrid Control Based on Deep Reinforcement Learning
por: Yao, Fulong, et al.
Publicado: (2024)

Probabilistic Reachability Analysis of Multi-scale Voltage Dynamics Using Reinforcement Learning
por: Hashima, Naoki, et al.
Publicado: (2026)

Model-Based Reinforcement Learning Control of Reaction-Diffusion Problems
por: Schenk, Christina, et al.
Publicado: (2024)

Robust Verification of Controllers under State Uncertainty via Hamilton-Jacobi Reachability Analysis
por: Lin, Albert, et al.
Publicado: (2025)