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Dive into the research topics where Florian Pommerening is active.

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Featured researches published by Florian Pommerening.


KI'09 Proceedings of the 32nd annual German conference on Advances in artificial intelligence | 2009

Right-of-way rules as use case for integrating GOLOG and qualitative reasoning

Florian Pommerening; Stefan Wölfl; Matthias Westphal

Agents interacting in a dynamically changing spatial environment often need to access the same spatial resources. A typical example is given by moving vehicles that meet at an intersection in a street network. In such situations right-of-way rules regulate the actions the vehicles involved may perform. For this application scenario we show how the Golog framework for reasoning about action and change can be enhanced by external reasoning services that implement techniques known from the domain of Qualitative Spatial Reasoning.


european conference on artificial intelligence | 2014

Optimal planning in the presence of conditional effects: extending LM-Cut with context splitting

Gabriele Röger; Florian Pommerening; Malte Helmert

The LM-Cut heuristic is currently the most successful heuristic in optimal STRIPS planning but it cannot be applied in the presence of conditional effects. Keyder, Hoffmann and Haslum recently showed that the obvious extensions to such effects ruin the nice theoretical properties of LM-Cut. We propose a new method based on context splitting that preserves these properties.


Archive | 2017

New perspectives on cost partitioning for optimal classical planning

Florian Pommerening

Admissible heuristics are the main ingredient when solving classical planning tasks optimally with heuristic search. There are many such heuristics, and each has its own strengths and weaknesses. As higher admissible heuristic values are more accurate, the maximum over several admissible heuristics dominates each individual one. Operator cost partitioning is a well-known technique to combine admissible heuristics in a way that dominates their maximum and remains admissible. But are there better options to combine the heuristics? We make three main contributions towards this question: Extensions to the cost partitioning framework can produce higher estimates from the same set of heuristics. Cost partitioning traditionally uses non-negative cost functions. We prove that this restriction is not necessary, and that allowing negative values as well makes the framework more powerful: the resulting heuristic values can be exponentially higher, and unsolvability can be detected even if all component heuristics have a finite value. We also generalize operator cost partitioning to transition cost partitioning, which can differentiate between different contexts in which an operator is used. Operator-counting heuristics reason about the number of times each operator is used in a plan. Many existing heuristics can be expressed in this framework, which gives new theoretical insight into their relationship. Different operator-counting heuristics can be easily combined within the framework in a way that dominates their maximum. Potential heuristics compute a heuristic value as a weighted sum over state features and are a fast alternative to operator-counting heuristics. Admissible and consistent potential heuristics for certain feature sets can be described in a compact way which means that the best heuristic from this class can be extracted in polynomial time. Both operator-counting and potential heuristics are closely related to cost partitioning. They offer a new look on cost-partitioned heuristics and already sparked research beyond their use as classical planning heuristics.


international conference on automated planning and scheduling | 2014

LP-based heuristics for cost-optimal planning

Florian Pommerening; Gabriele Röger; Malte Helmert; Blai Bonet


international joint conference on artificial intelligence | 2013

Getting the most out of pattern databases for classical planning

Florian Pommerening; Gabriele Röger; Malte Helmert


international conference on automated planning and scheduling | 2012

Optimal planning for delete-free tasks with incremental LM-cut

Florian Pommerening; Malte Helmert


national conference on artificial intelligence | 2015

From non-negative to general operator cost partitioning

Florian Pommerening; Malte Helmert; Gabriele Röger; Jendrik Seipp


international conference on automated planning and scheduling | 2015

New optimization functions for potential heuristics

Jendrik Seipp; Florian Pommerening; Malte Helmert


international conference on automated planning and scheduling | 2015

A normal form for classical planning tasks

Florian Pommerening; Malte Helmert


Archive | 2015

Linear programming for heuristics in optimal planning

Gabriele Röger; Florian Pommerening

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Blai Bonet

Simón Bolívar University

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