3 citations · 3 across the 14 of their papers we have counts for
4 papers · 1 filter
Incremental Data-Driven Policy Synthesis via Game Abstractions
Irmak Sağlam, 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…
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…
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…