7 papers
Sound Probabilistic Safety Bounds for Large Language Models
Mahdi Nazeri, Anne-Kathrin Schmuck, Sadegh Soudjani +1
We propose a novel framework for computing rigorous bounds on the probability that a large language model (LLM) generates harmful output to a given prompt. We study a new applicati…
Incremental Data-Driven Policy Synthesis via Game Abstractions
Irmak SaÄlam, Mahdi Nazeri, Alessandro Abate +2
We address the synthesis of control policies for unknown discrete-time stochastic dynamical systems to satisfy temporal logic objectives. We present a data-driven, abstraction-base…
Data-Driven Abstraction and Synthesis for Stochastic Systems with Unknown Dynamics
Mahdi Nazeri, Thom Badings, Anne-Kathrin Schmuck +2
We study the automated abstraction-based synthesis of correct-by-construction control policies for stochastic dynamical systems with unknown dynamics. Our approach is to learn an a…
Data-Driven Yet Formal Policy Synthesis for Stochastic Nonlinear Dynamical Systems
Mahdi Nazeri, Thom Badings, Sadegh Soudjani +1
The automated synthesis of control policies for stochastic dynamical systems presents significant challenges. A standard approach is to construct a finite-state abstraction of the…
Probabilistic Alternating Simulations for Policy Synthesis in Uncertain Stochastic Dynamical Systems
Thom Badings, Alessandro Abate
A classical approach to formal policy synthesis in stochastic dynamical systems is to construct a finite-state abstraction, often represented as a Markov decision process (MDP). Th…
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…