Jörg Hoffmann

Explaining Soft-Goal Conflicts through Constraint Relaxations

2022

Recent work suggests to explain trade-offs between soft-goals in terms of their conflicts, i.e., minimal unsolvable soft-goal subsets. But this does not explain the conflicts themselves: Why can a given set of soft-goals not be …

Choosing the Initial State for Online Replanning

2021 · Proceedings of the AAAI Conference on Artificial Intelligence

The need to replan arises in many applications. However, in the context of planning as heuristic search, it raises an annoying problem: if the previous plan is still executing, what should the new plan search …

Automated Safety Verification of Programs Invoking Neural Networks

2021 · Lecture notes in computer science

Abstract State-of-the-art program-analysis techniques are not yet able to effectively verify safety properties of heterogeneous systems, that is, systems with components implemented using diverse technologies. This shortcoming is pinpointed by programs invoking neural networks despite …

Specifying and Testing $k$-Safety Properties for Machine-Learning Models

2022 · arXiv (Cornell University)

Machine-learning models are becoming increasingly prevalent in our lives, for instance assisting in image-classification or decision-making tasks. Consequently, the reliability of these models is of critical importance and has resulted in the development of numerous …

Improved Generalized Planning with LLMs Through Strategy Refinement and Reflection

2026 · Proceedings of the International Conference on Automated Planning and Scheduling

LLMs have recently been used to generate Python programs representing generalized plans in PDDL planning, i.e., plans that generalize across the tasks of a given PDDL domain. Previous work proposed a framework consisting of three …