Copertina

On the Optimality of Uncertain MDP Abstractions

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Gracia, Ibon, Lahijanian, Morteza
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Systems and Control
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Data-Driven Control via Conditional Mean Embeddings: Formal Guarantees via Uncertain MDP Abstraction
di: Gracia, Ibon, et al.
Pubblicazione: (2025)

Beyond Interval MDPs: Tight and Efficient Abstractions of Stochastic Systems
di: Gracia, Ibon, et al.
Pubblicazione: (2025)

Data-Driven Strategy Synthesis for Stochastic Systems with Unknown Nonlinear Disturbances
di: Gracia, Ibon, et al.
Pubblicazione: (2024)

Provably Safe Motion Planning Under Unknown Disturbances
di: Gracia, Ibon, et al.
Pubblicazione: (2026)

A Unifying Perspective for Safety of Stochastic Systems: From Barrier Functions to Finite Abstractions
di: Laurenti, Luca, et al.
Pubblicazione: (2023)

Temporal Logic Control for Nonlinear Stochastic Systems Under Unknown Disturbances
di: Gracia, Ibon, et al.
Pubblicazione: (2024)

Efficient Strategy Synthesis for Switched Stochastic Systems with Distributional Uncertainty
di: Gracia, Ibon, et al.
Pubblicazione: (2022)

Training with Hard Constraints: Learning Neural Certificates and Controllers for SDEs
di: Kong, Chun-Wei, et al.
Pubblicazione: (2026)

IntervalMDP.jl: Accelerated Value Iteration for Interval Markov Decision Processes
di: Mathiesen, Frederik Baymler, et al.
Pubblicazione: (2024)

On Polynomial Stochastic Barrier Functions: Bernstein Versus Sum-of-Squares
di: Amorese, Peter, et al.
Pubblicazione: (2025)

Learning Nonlinear Continuous-Time Systems for Formal Uncertainty Propagation and Probabilistic Evaluation
di: Amorese, Peter, et al.
Pubblicazione: (2026)

Learning Markov Processes as Sum-of-Square Forms for Analytical Belief Propagation
di: Amorese, Peter, et al.
Pubblicazione: (2026)

Universal Learning of Stochastic Dynamics for Exact Belief Propagation using Bernstein Normalizing Flows
di: Amorese, Peter, et al.
Pubblicazione: (2025)

Learning-Based Shielding for Safe Autonomy under Unknown Dynamics
di: Reed, Robert, et al.
Pubblicazione: (2024)

Piecewise Control Barrier Functions for Stochastic Systems
di: Mazouz, Rayan, et al.
Pubblicazione: (2025)

Time-Varying Reach-Avoid Control Certificates for Stochastic Systems
di: Mazouz, Rayan, et al.
Pubblicazione: (2026)

Promises of Deep Kernel Learning for Control Synthesis
di: Reed, Robert, et al.
Pubblicazione: (2023)

Uncertainty Propagation in Stochastic Systems via Mixture Models with Error Quantification
di: Figueiredo, Eduardo, et al.
Pubblicazione: (2024)

Bayesian Diagnosability and Active Fault Identification
di: Kong, Chun-Wei, et al.
Pubblicazione: (2025)

StochasticBarrier.jl: A Toolbox for Stochastic Barrier Function Synthesis
di: Mazouz, Rayan, et al.
Pubblicazione: (2026)

A Novel MDP Decomposition Framework for Scalable UAV Mission Planning in Complex and Uncertain Environments
di: Quamar, Md Muzakkir, et al.
Pubblicazione: (2025)

Formal Verification of Unknown Dynamical Systems via Gaussian Process Regression
di: Skovbekk, John, et al.
Pubblicazione: (2021)

Interval Markov Decision Processes with Continuous Action-Spaces
di: Delimpaltadakis, Giannis, et al.
Pubblicazione: (2022)

Falsification of Autonomous Systems in Rich Environments
di: Elimelech, Khen, et al.
Pubblicazione: (2024)

Safety Guarantees for Neural Network Dynamic Systems via Stochastic Barrier Functions
di: Mazouz, Rayan, et al.
Pubblicazione: (2022)

An MDP Model for Censoring in Harvesting Sensors: Optimal and Approximated Solutions
di: Fernandez-Bes, Jesus, et al.
Pubblicazione: (2025)

Efficiency through Uncertainty: Scalable Formal Synthesis for Stochastic Hybrid Systems
di: Cauchi, Nathalie, et al.
Pubblicazione: (2019)

Regret Optimal Control for Uncertain Stochastic Systems
di: Martin, Andrea, et al.
Pubblicazione: (2023)

Data-driven Interval MDP for Robust Control Synthesis
di: Coppola, Rudi, et al.
Pubblicazione: (2024)

Parameter Privacy-Preserving Data Sharing: A Particle-Belief MDP Formulation
di: Yu, Haokun, et al.
Pubblicazione: (2026)

Data-Driven Permissible Safe Control with Barrier Certificates
di: Mazouz, Rayan, et al.
Pubblicazione: (2024)

Robust Distributed Sub-Optimal Coordination of Linear Agents with Uncertain Input Nonlinearities
di: Namba, Takumi
Pubblicazione: (2026)

Optimal Network Expansion Planning Considering Uncertain Dynamic Thermal Line Rating
di: Baharvandi, Arash, et al.
Pubblicazione: (2024)

Two-Stage Stochastic Optimal Power Flow for Microgrids With Uncertain Wildfire Effects
di: Chowdhury, Sifat, et al.
Pubblicazione: (2024)

An MDP-Based Approach for Distribution System Control with PV Generation and Battery Storage
di: Sosnowski, Robert, et al.
Pubblicazione: (2024)

Tsallis Entropy Regularization for Linearly Solvable MDP and Linear Quadratic Regulator
di: Hashizume, Yota, et al.
Pubblicazione: (2024)

Learning Optimal Scheduling Policy for Remote State Estimation under Uncertain Channel Condition
di: Wu, Shuang, et al.
Pubblicazione: (2018)

AoI-MDP: An AoI Optimized Markov Decision Process (Student Abstract)
di: Ding, Yimian, et al.
Pubblicazione: (2026)

On an Abstraction of Lyapunov and Lagrange Stability
di: Bin, Michelangelo, et al.
Pubblicazione: (2025)

Hierarchical Decision-Making under Uncertainty: A Hybrid MDP and Chance-Constrained MPC Approach
di: Li, Siyuan, et al.
Pubblicazione: (2026)