1 citations · 1 across the 10 of their papers we have counts for
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Certified Stochastic Control via Covariance Steering with Pick-to-Learn
Chun-Wei Kong, Zachary Donovan, Morteza Lahijanian +1
We present CS-P2L, a framework coupling covariance steering (CS) with the Pick-to-Learn (P2L) meta-algorithm for certified controller synthesis over high-fidelity stochastic simula…
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…
StochasticBarrier.jl: A Toolbox for Stochastic Barrier Function Synthesis
Rayan Mazouz, Frederik Baymler Mathiesen, Luca Laurenti +1
We present StochasticBarrier.jl, an open-source Julia-based toolbox for generating Stochastic Barrier Functions (SBFs) for safety verification of discrete-time stochastic systems w…
Probabilistically Safe Vehicle Control in a Hostile Environment
Igor Cizelj, Xu Chu Ding, Morteza Lahijanian +2
In this paper we present an approach to control a vehicle in a hostile environment with static obstacles and moving adversaries. The vehicle is required to satisfy a mission object…