7 papers · 1 filter
On the Optimality of Uncertain MDP Abstractions
Ibon Gracia, Morteza Lahijanian
We study the asymptotic optimality of abstraction-based control synthesis algorithms. Specifically, we consider uncertain MDP (UMDP) abstraction, and investigate whether refinement…
Training with Hard Constraints: Learning Neural Certificates and Controllers for SDEs
Chun-Wei Kong, Sebastian Escobar, Ibon Gracia +2
Due to their expressive power, neural networks (NNs) are promising templates for functional optimization problems, particularly for reach-avoid certificate generation for systems g…
Data-Driven Control via Conditional Mean Embeddings: Formal Guarantees via Uncertain MDP Abstraction
Ibon Gracia, Morteza Lahijanian
Controlling stochastic systems with unknown dynamics and under complex specifications is specially challenging in safety-critical settings, where performance guarantees are essenti…
Beyond Interval MDPs: Tight and Efficient Abstractions of Stochastic Systems
Ibon Gracia, Morteza Lahijanian
This work addresses the general problem of control synthesis for continuous-space, discrete-time stochastic systems with probabilistic guarantees via finite abstractions. While est…
Temporal Logic Control for Nonlinear Stochastic Systems Under Unknown Disturbances
Ibon Gracia, Luca Laurenti, Manuel Mazo +2
In this paper, we present a novel framework to synthesize robust strategies for discrete-time nonlinear systems with random disturbances that are unknown, against temporal logic sp…
Data-Driven Strategy Synthesis for Stochastic Systems with Unknown Nonlinear Disturbances
Ibon Gracia, Dimitris Boskos, Luca Laurenti +1
In this paper, we introduce a data-driven framework for synthesis of provably-correct controllers for general nonlinear switched systems under complex specifications. The focus is…
Efficient Strategy Synthesis for Switched Stochastic Systems with Distributional Uncertainty
Ibon Gracia, Dimitris Boskos, Morteza Lahijanian +2
We introduce a framework for the control of discrete-time switched stochastic systems with uncertain distributions. In particular, we consider stochastic dynamics with additive noi…