Foundations of Artificial Intelligence (FAI) Group

Daniel Höller

Research Interests

I am interested in many practical and theoretical aspects of planning and related tasks like plan explanation, plan recognition, plan repair and plan verification.

So far, my work mainly focused on hierarchical planning, especially HTN planning. In this area, I have been working on solvers based on heuristic search and based on transformations to propositional logic, on expressivity analysis of planning formalisms, and on problem compilation.

Short CV

Awards

• The paper A Generic Method to Guide HTN Progression Search with Classical Heuristics by Daniel Höller, Pascal Bercher, Gregor Behnke, and Susanne Biundo won the ICAPS 2018 Best Student Paper Award.
  It shows how to use heuristics from classical planning to guide a search in hierarchical planning.
• The paper Plan and Goal Recognition as HTN Planning by Daniel Höller, Gregor Behnke, Pascal Bercher, and Susanne Biundo won the ICTAI 2018 CV Ramamoorthy Best Paper Award.
  It introduces an approach to transform plan and goal recognition problems into hierarchical planning problems.
• The paper HTN Plan Repair via Model Transformation by D. Höller, P. Bercher, G. Behnke, and S. Biundo was shortlisted for Best Paper Award (3rd place) at the 2020 German Conference on Artificial Intelligence (KI).
  It shows how to transform plan repair problems into hierarchical planning problems.

Software