9 papers
Infinite Trace Objectives with Finite Trace Techniques: Translating LTL to LTLf+
Christoph Weinhuber, Maximilian Prokop, Giuseppe De Giacomo +1
Linear Temporal Logic (LTL) is one of the most widely adopted languages for specifying temporal extended objectives in AI, with applications ranging from reactive synthesis to stoc…
Formal Foundations of Agentic Business Process Management
Giuseppe De Giacomo, Timotheus Kampik, Lukas Kirchdorfer +2
Just like traditional BPM systems, agentic BPM systems are built around a specification of the process under consideration. Their distinguishing feature, however, is that the execu…
Reasoning models do not yet follow their reasoning in autonomous driving: The KITScenes LongTail Dataset
Royden Wagner, Omer Sahin Tas, Jaime Villa +20
Handling rare events is the central open challenge in autonomous driving. Reasoning models, which generate explicit chains of reasoning before acting, promise to generalize to such…
Semantically Labelled Automata for Multi-Task Reinforcement Learning with LTL Instructions
Alessandro Abate, Giuseppe De Giacomo, Mathias Jackermeier +3
We study multi-task reinforcement learning (RL), a setting in which an agent learns a single, universal policy capable of generalising to arbitrary, possibly unseen tasks. We consi…
Multi-Property Synthesis
Christoph Weinhuber, Yannik Schnitzer, Alessandro Abate +3
We study LTLf synthesis with multiple properties, where satisfying all properties may be impossible. Instead of enumerating subsets of properties, we compute in one fixed-point com…
Good-for-MDP State Reduction for Stochastic LTL Planning
Christoph Weinhuber, Giuseppe De Giacomo, Yong Li +2
We study stochastic planning problems in Markov Decision Processes (MDPs) with goals specified in Linear Temporal Logic (LTL). The state-of-the-art approach transforms LTL formulas…