Arbeitsgruppe Grundlagen der Künstlichen Intelligenz

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2008

• Matthias Westphal und Stefan Wölfl.
  Bipath Consistency Revisited.
  In Proceedings of the ECAI'08 Workshop on Spatial and Temporal Reasoning. Patras, Greece 2008.
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  In the field of qualitative spatial and temporal reasoning combinations of constraint calculi have attracted considerable research interest in recent years. Beside combinations of spatial and temporal calculi, it is an important research topic to develop generic methods for combining calculi dealing with different spatial aspects. The prototypical example is the combination of the region connection calculus RCC8 and the point algebra first discussed by Gerevini and Renz, which allows to represent, and reason about, topological and size information about spatially extended objects. To solve constraints in this calculus, Gerevini and Renz also proposed an algorithm, the bipath consistency algorithm, which allows for deciding consistency of a given constraint network for specific sets of relations combining topology and size. In this article we will compare the "bipath consistency"-based combination method to the standard method, which is to combine calculi by generating a new calculus and applying the standard path consistency method. Gerevini and Renz's calculus combining topological and size information will serve as the running example of such combinations and also as a test case for an empirical analysis.

• Zeno Gantner, Matthias Westphal und Stefan Wölfl.
  GQR - A Fast Reasoner for Binary Qualitative Constraint Calculi.
  In Proceedings of the AAAI'08 Workshop on Spatial and Temporal Reasoning. Chicago, USA 2008.
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  GQR (Generic Qualitative Reasoner) is a solver for binary qualitative constraint networks. GQR takes a calculus description and one or more constraint networks as input, and tries to solve the networks using the path consistency method and (heuristic) backtracking. In contrast to specialized reasoners, it offers reasoning services for different qualitative calculi, which means that these calculi are not hard-coded into the reasoner. Currently, GQR supports arbitrary binary constraint calculi developed for spatial and temporal reasoning, such as calculi from the RCC family, the intersection calculi, Allen's interval algebra, cardinal direction calculi, and calculi from the OPRA family. New calculi can be added to the system by specifications in a simple text format or in an XML file format. The tool is designed and implemented with genericity and extensibility in mind, while preserving efficiency and scalability. The user can choose between different data structures and heuristics, and new ones can be easily added to the object-oriented framework. GQR is free software distributed under the terms of the GNU General Public License.

• Silvia Richter, Malte Helmert und Matthias Westphal.
  Landmarks Revisited.
  In Proceedings of the 23rd AAAI Conference on Artificial Intelligence (AAAI 2008), S. 975-982. AAAI Press 2008.
  Note: After publication, we found a bug in our implementation that affects the results in the columns "CG heuristic/local" and "blind heuristic/local" of Table 1. The version of the paper available for download here corrects these errors.
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  Landmarks for propositional planning tasks are variable assignments that must occur at some point in every solution plan. We propose a novel approach for using landmarks in planning by deriving a pseudo-heuristic and combining it with other heuristics in a search framework. The incorporation of landmark information is shown to improve success rates and solution qualities of a heuristic planner. We furthermore show how additional landmarks and orderings can be found using the information present in multi-valued state variable representations of planning tasks. Compared to previously published approaches, our landmark extraction algorithm provides stronger guarantees of correctness for the generated landmark orderings, and our novel use of landmarks during search solves more planning tasks and delivers considerably better solutions.