activity
20242026
collaborators

5 papers

cs.LG2026

Flowing Through States: Neural ODE Regularization for Reinforcement Learning

Mohamed Ghanem, Bernd Finkbeiner

Neural networks applied to sequential decision-making tasks typically rely on latent representations of environment states. While environment dynamics dictate how semantic states e…

cs.LG2026

Natural Synthesis: Outperforming Reactive Synthesis Tools with Large Reasoning Models

Frederik Schmitt, Matthias Cosler, Niklas Metzger +4

Reactive synthesis, the problem of automatically constructing a hardware circuit from a logical specification, is a long-standing challenge in formal verification. It is elusive fo…

cs.LO2025

Universal Safety Controllers with Learned Prophecies

Bernd Finkbeiner, Niklas Metzger, Satya Prakash Nayak +1

\emph{Universal Safety Controllers (USCs)} are a promising logical control framework that guarantees the satisfaction of a given temporal safety specification when applied to any r…

cs.LO2025

Synthesis of Universal Safety Controllers

Bernd Finkbeiner, Niklas Metzger, Satya Prakash Nayak +1

The goal of logical controller synthesis is to automatically compute a control strategy that regulates the discrete, event-driven behavior of a given plant s.t. a temporal logic sp…

cs.LO2024

Information Flow Guided Synthesis with Unbounded Communication

Bernd Finkbeiner, Niklas Metzger, Yoram Moses

Information flow guided synthesis is a compositional approach to the automated construction of distributed systems where the assumptions between the components are captured as info…