This page contains all publications of the institute. If you are searching for a particular paper that might have been written before the researcher joined us, please visit his or her individual page.

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Publications of the Institute of Artificial Intelligence

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Nothdurft, Florian, Behnke, Gregor, Bercher, Pascal, Biundo, Susanne and Minker, Wolfgang
The Interplay of User-Centered Dialog Systems and AI Planning
Proceedings of the 16th Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL) , page 344--353.
Publisher: Association for Computational Linguistics,
September 2015

Tags: SFB-TRR-62,Planning

Abstract: Technical systems evolve from simple dedicated task solvers to cooperative and competent assistants, helping the user with increasingly complex and demanding tasks. For this, they may proactively take over some of the users responsibilities and help to find or reach a solution for the user’s task at hand, using e.g., Artificial Intelligence (AI) Planning techniques. However, this intertwining of user-centered dialog and AI planning systems, often called mixed-initiative planning (MIP), does not only facilitate more intelligent and competent systems, but does also raise new questions related to the alignment of AI and human problem solving. In this paper, we describe our approach on integrating AI Planning techniques into a dialog system, explain reasons and effects of arising problems, and provide at the same time our solutions resulting in a coherent, userfriendly and efficient mixed-initiative system. Finally, we evaluate our MIP system and provide remarks on the use of explanations in MIP-related phenomena.

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Glodek, Michael, Honold, Frank, Geier, Thomas, Krell, Gerald, Nothdurft, Florian, Reuter, Stephan, Schüssel, Felix, Hörnle, Thilo, Dietmayer, Klaus, Minker, Wolfgang, Biundo, Susanne, Weber, Michael, Palm, Günther and Schwenker, Friedhelm
Fusion paradigms in cognitive technical systems for human–computer interaction
Neurocomputing, 161(0):17 - 37
2015
ISSN: 0925-2312

Keywords: Human–computer interaction

Abstract: Abstract Recent trends in human–computer interaction (HCI) show a development towards cognitive technical systems (CTS) to provide natural and efficient operating principles. To do so, a CTS has to rely on data from multiple sensors which must be processed and combined by fusion algorithms. Furthermore, additional sources of knowledge have to be integrated, to put the observations made into the correct context. Research in this field often focuses on optimizing the performance of the individual algorithms, rather than reflecting the requirements of CTS. This paper presents the information fusion principles in CTS architectures we developed for Companion Technologies. Combination of information generally goes along with the level of abstractness, time granularity and robustness, such that large CTS architectures must perform fusion gradually on different levels — starting from sensor-based recognitions to highly abstract logical inferences. In our CTS application we sectioned information fusion approaches into three categories: perception-level fusion, knowledge-based fusion and application-level fusion. For each category, we introduce examples of characteristic algorithms. In addition, we provide a detailed protocol on the implementation performed in order to study the interplay of the developed algorithms.

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Ulmschneider, Klaus, Michelberger, Bernd, Glimm, Birte, Mutschler, Bela and Reichert, Manfred
On Maintaining Semantic Networks: Challenges, Algorithms, Use Cases
International Journal of Web Information Systems, 11(3):291-326
2015

Tags: AutomatedReasoning

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Kazakov, Yevgeny and Klinov, Pavel
Advancing {ELK}: Not Only Performance Matters
In Diego Calvanese and Boris Konev, editor, DL Volume 1350 of CEUR Workshop Proceedings
Publisher: CEUR-WS.org,
2015

Tags: KnowledgeModeling, ELK, LiveOntologies

Abstract: This paper reports on the recent development of ELK, a consequence-based reasoner for $\mathcal{EL^+_\bot}$ ontologies. It covers novel reasoning techniques which aim at improving efficiency and providing foundation for new reasoning services. On the former front we present a simple optimization for handling of role composition axioms, such as transitivity, which substantially reduces the number of rule applications. For the latter, we describe a new rule application strategy that takes advantage of concept definitions to avoid many redundant inferences without making rules dependent on derived conclusions. This improvement is not visible to the end user but considerably simplifies implementation for incremental reasoning and proof generation. We also present a rewriting of low-level inferences used by ELK to higher-level proofs that can be defined in the standard DL syntax, and thus be used for automatic verification of reasoning results or (visual) ontology debugging. We demonstrate the latter capability using a new ELK Prot\'eg\'e plugin.

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Behnke, Gregor, Ponomaryov, Denis, Schiller, Marvin, Bercher, Pascal, Nothdurft, Florian, Glimm, Birte and Biundo, Susanne
Coherence Across Components in Cognitive Systems – One Ontology to Rule Them All
Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI 2015)
Publisher: AAAI Press,
2015

Tags: SFB-TRR-62,Planning,AutomatedReasoning

Abstract: The integration of the various specialized components of cognitive systems poses a challenge, in particular for those architectures that combine planning, inference, and human-computer interaction (HCI). An approach is presented that exploits a single source of common knowledge contained in an ontology. Based upon the knowledge contained in it, specialized domain models for the cognitive systems’ components can be generated automatically. Our integration targets planning in the form of hierarchical planning, being well-suited for HCI as it mimics planning done by humans. We show how the hierarchical structures of such planning domains can be (partially) inferred from declarative background knowledge. The same ontology furnishes the structure of the interaction between the cognitive system and the user. First, explanations of plans presented to users are enhanced by ontology explanations. Second, a dialog domain is created from the ontology coherent with the planning domain. We demonstrate the application of our technique in a fitness training scenario.

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Steigmiller, Andreas, Glimm, Birte and Liebig, Thorsten
Completion Graph Caching for Expressive Description Logics
Proceedings of the 28th International Workshop on Description Logics (DL 2015)
Publisher: CEUR Workshop Proceedings,
2015

Tags: AutomatedReasoning

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Bercher, Pascal
Hybrid Planning -- Theoretical Foundations and Practical Applications
Doctoral Consortium at ICAPS 2015
2015

Tags: SFB-TRR-62,Planning

Abstract: The thesis presents a novel set-theoretic formalization of (propositional) hybrid planning – a planning framework that fuses Hierarchical Task Network (HTN) planning with Partial-Order Causal-Link (POCL) planning. Several sub classes thereof are identified that capture well-known problems such as HTN planning and POCL planning. For these problem classes, the complexity of the plan-existence problem is investigated, i.e., the problem of deciding whether there exists a solution for a given planning problem. For solving the problems of the respective problem classes, a hybrid planning algorithm is presented. Its search is guided by informed heuristics. Several such heuristics are introduced, both for POCL planning problems (i.e., problems without task hierarchy) and for hybrid planning problems (i.e., heuristics that are "hierarchy-aware").

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Behnke, Gregor, Bercher, Pascal, Biundo, Susanne, Glimm, Birte, Ponomaryov, Denis and Schiller, Marvin
Integrating Ontologies and Planning for Cognitive Systems
Proceedings of the 28th International Workshop on Description Logics (DL 2015)
Publisher: CEUR Workshop Proceedings,
2015

Tags: AutomatedReasoning, Planning, SFB-TRR-62

Abstract: We present an approach for integrating ontological reasoning and planning within cognitive systems. Patterns and mechanisms that suitably link planning domains and interrelated knowledge in an ontology are devised. In particular, this enables the use of (standard) ontology reasoning for extending a (hierarchical) planning domain. Furthermore, explanations of plans generated by a cognitive system benefit from additional explanations relying on background knowledge in the ontology and inference. An application of this approach in the domain of fitness training is presented.

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Geier, Thomas, Richter, Felix and Biundo, Susanne
Locally Conditioned Belief Propagation
Proceedings of the 31st Conference on Uncertainty in Artificial Intelligence (UAI)
2015

Keywords: probablistic inference, belief propagation, approximate inference, graphical models

Abstract: Conditioned Belief Propagation (CBP) is an algorithm for approximate inference in probabilistic graphical models. It works by conditioning on a subset of variables and solving the remainder using loopy Belief Propagation. Unfortunately, CBP's runtime scales exponentially in the number of conditioned variables. Locally Conditioned Belief Propagation (LCBP) approximates the results of CBP by treating conditions locally, and in this way avoids the exponential blow-up. We formulate LCBP as a variational optimization problem and derive a set of update equations that can be used to solve it. We show empirically that LCBP delivers results that are close to those obtained from CBP, while the computational cost scales favorably with problem size.

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Glimm, Birte, Kazakov, Yevgeny, Kollia, Ilianna and Stamou, Giorgos
Lower and Upper Bounds for SPARQL Queries over OWL Ontologies
Proceedings of the 28th International Workshop on Description Logics (DL 2015)
Publisher: CEUR Workshop Proceedings,
2015

Keywords: Description Logics, Query Answering, Semantic Web, SPARQL

Tags: AutomatedReasoning

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