Mobile manipulation problems involving many objects are challenging to solve due to the
high dimensionality and multi-modality of their hybrid configuration spaces. Planners that …

Unavoidable dead-ends are common in many probabilistic planning problems, eg when
actions may fail or when operating under resource constraints. An important objective in …

Liste der Autoren Page 1 Liste der Autoren Clemens Beckstein Gerhard Brewka Christian
Borgelt Wolfram Burgard Hans-Dieter Burkhard Stephan Busemann Thomas Christaller Leonie …

We generalise the interval-based relaxation to sequential numeric planning problems with
non-linear conditions and effects, and cyclic dependencies. This effectively removes all the …

This paper studies novel subgoaling relaxations for automated planning with propositional
and numeric state variables. Subgoaling relaxations address one source of complexity of the …

To date, delete relaxation underlies some of the most effective heuristics for deterministic
planning. Despite its success, however, delete relaxation has significant pitfalls in many …

In many real-world hybrid (mixed discrete continuous) planning problems such as Reservoir
Control, Heating, Ventilation and Air Conditioning (HVAC), and Navigation, it is difficult to …

Graph learning is naturally well suited for use in symbolic, object-centric planning due to its
ability to exploit relational structures exhibited in planning domains and to take as input …

The LM-cut heuristic, both alone and as part of the operator counting framework, represents
one of the most successful heuristics for classical planning. In this paper, we generalize LM …

Planning for hybrid systems is important for dealing with real-world applications, and PDDL+
supports this representation of domains with mixed discrete and continuous dynamics. In …