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• University of Freiburg
• Faculty of Engineering
• Department of Computer Science

Thomas Keller – Publications

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2011

• Danijel Skocaj, Matej Kristan, Alen Vrecko, Marko Mahnic, Miroslav Janicek, Geert-Jan M. Kruijff, Marc Hanheide, Nick Hawes, Thomas Keller, Michael Zillich and Kai Zhou.
  A system for interactive learning in dialogue with a tutor.
  In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2011). 2011.
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  In this paper we present representations and mechanisms that facilitate continuous learning of visual concepts in dialogue with a tutor and show the implemented robot system. We present how beliefs about the world are created by processing visual and linguistic information and show how they are used for planning system behaviour with the aim at satisfying its internal drive -- to extend its knowledge. The system facilitates different kinds of learning initiated by the human tutor or by the system itself. We demonstrate these principles in the case of learning about object colours and basic shapes.

• Thomas Keller and Patrick Eyerich.
  A Polynomial All Outcome Determinization for Probabilistic Planning.
  In Fahiem Bacchus, Carmel Domshlak, Stefan Edelkamp and Malte Helmert (eds.), Proceedings of the 21th International Conference on Automated Planning and Scheduling (ICAPS 2011), pp. 331-334. AAAI Press 2011.
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  Most predominant approaches in probabilistic planning utilize techniques from the more thoroughly investigated field of classical planning by determinizing the problem at hand. In this paper, we present a method to map probabilistic operators to an equivalent set of probabilistic operators in a novel normal form, requiring polynomial time and space. From this, we directly derive a determinization which can be used for, \eg, replanning strategies incorporating a classical planning system. Unlike previously described all outcome determinizations, the number of deterministic operators is not exponentially but polynomially bounded in the number of parallel probabilistic effects, enabling the use of more sophisticated determinization-based techniques in the future.

2010

• Thomas Keller, Patrick Eyerich and Bernhard Nebel.
  Task Planning for an Autonomous Service Robot.
  In Rüdiger Dillmann, Jürgen Beyerer, Uwe Hanebeck and Tanja Schultz (eds.), Proceedings on the 33rd Annual German Conference on Artificial Intelligence (KI 2010), pp. 358-365. Springer-Verlag 2010.
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  In the DESIRE project an autonomous robot capable of performing service tasks in a typical kitchen environment has been developed. The overall system consists of various loosely coupled subcomponents providing particular features like manipulating objects or recognizing and interacting with humans. To bring all these subcomponents together to act as monolithic system, a high-performance planning system has been implemented. In this paper, we present this system’s basic architecture and some advanced extensions necessary to cope with the various challenges arising in dynamic and uncertain environments like those a real world service robot is usually faced with.

• Patrick Eyerich, Thomas Keller and Malte Helmert.
  High-Quality Policies for the Canadian Traveler's Problem.
  In Maria Fox and David Poole (eds.), Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence (AAAI 2010), pp. 51-58. AAAI Press 2010.
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  We consider the stochastic variant of the Canadian Traveler's Problem, a path planning problem where adverse weather can cause some roads to be untraversable. The agent does not initially know which roads can be used. However, it knows a probability distribution for the weather, and it can observe the status of roads incident to its location. The objective is to find a policy with low expected travel cost.

  We introduce and compare several algorithms for the stochastic CTP. Unlike the optimistic approach most commonly considered in the literature, the new approaches we propose take uncertainty into account explicitly. We show that this property enables them to generate policies of much higher quality than the optimistic one, both theoretically and experimentally.

• Patrick Eyerich, Thomas Keller and Malte Helmert.
  High-Quality Policies for the Canadian Traveler's Problem (Extended Abstract).
  In Ariel Felner and Nathan Sturtevant (eds.), Proceedings of the Third Annual Symposium on Combinatorial Search (SoCS 2010), pp. 147-148. AAAI Press 2010.
  Extended abstract of the AAAI paper by the same name.
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• Moritz Göbelbecker, Thomas Keller, Patrick Eyerich, Michael Brenner and Bernhard Nebel.
  Coming Up with Good Excuses: What To Do When No Plan Can be Found.
  In Ronen Brafman, Héctor Geffner, Jörg Hoffmann and Henry Kautz (eds.), Proceedings of the 20th International Conference on Automated Planning and Scheduling (ICAPS 2010), pp. 81-88. AAAI Press 2010.
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  When using a planner-based agent architecture, many things can go wrong. First and foremost, an agent might fail to execute one of the planned actions for some reasons. Even more annoying, however, is a situation where the agent is incompetent, i.e., unable to come up with a plan. This might be due to the fact that there are principal reasons that prohibit a successful plan or simply because the task's description is incomplete or incorrect. In either case, an explanation for such a failure would be very helpful. We will address this problem and provide a formalization of coming up with excuses for not being able to find a plan. Based on that, we will present an algorithm that is able to find excuses and demonstrate that such excuses can be found in practical settings in reasonable time.

• Patrick Eyerich, Thomas Keller and Malte Helmert.
  High-Quality Policies for the Canadian Traveler's Problem.
  In Proceedings of the ICAPS-2010 Workshop on Planning and Scheduling Under Uncertainty. 2010.
  Superseded by the AAAI 2010 paper by the same name.
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  We consider the stochastic variant of the Canadian Traveler's Problem, a path planning problem where adverse weather can cause some roads to be untraversable. The agent does not initially know which roads can be used. However, it knows a probability distribution for the weather, and it can observe the status of roads incident to its location. The objective is to find a policy with low expected travel cost.

  We introduce and compare several algorithms for the stochastic CTP. Unlike the optimistic approach most commonly considered in the literature, the new approaches we propose take uncertainty into account explicitly. We show that this property enables them to generate policies of much higher quality than the optimistic one, both theoretically and experimentally.

• Patrick Eyerich, Thomas Keller and Bernhard Nebel.
  Combining Action and Motion Planning via Semantic Attachments.
  In Proceedings of the Workshop on Combining Action and Motion Planning at ICAPS 2010 (CAMP 2010), p. 19. 2010.
  Extended Abstract.
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2009

• Christian Dornhege, Patrick Eyerich, Thomas Keller, Sebastian Trüg, Michael Brenner and Bernhard Nebel.
  Semantic Attachments for Domain-Independent Planning Systems.
  In Proceedings of the 19th International Conference on Automated Planning and Scheduling (ICAPS 2009), pp. 114-121. AAAI Press 2009.
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  Solving real-world problems using symbolic planning often requires a simplified formulation of the original problem, since certain subproblems cannot be represented at all or only in a way leading to inefficiency. For example, manipulation planning may appear as a subproblem in a robotic planning context or a packing problem can be part of a logistics task. In this paper we propose an extension of PDDL for specifying semantic attachments. This allows the evaluation of grounded predicates as well as the change of fluents by externally specified functions. Furthermore, we describe a general schema of integrating semantic attachments into a forward-chaining planner and report on our experience of adding this extension to the planners FF and Temporal Fast Downward. Finally, we present some preliminary experiments using semantic attachments.

2008

• Thomas Keller.
  Optimales domänenspezifisches Planen in der Transport- und Routenplanungsfamilie.
  Diploma thesis, Albert-Ludwigs-Universität, Freiburg, Germany 2008.
  In German.
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• Thomas Keller and Sebastian Kupferschmid.
  Automatic Bidding for the Game of Skat.
  In Andreas R. Dengel, Karsten Berns, Thomas M. Breuel, Frank Bomarius and Thomas R. Roth-Berghofer (eds.), Proceedings of the 31st Annual German Conference on Artificial Intelligence (KI 2008), pp. 95-102. Springer-Verlag 2008.
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  In recent years, researchers started to study the game of Skat. The strength of existing Skat playing programs is definitely the card play phase. The bidding phase, however, was treated quite poorly so far. This is a severe drawback since bidding abilities influence the overall playing performance drastically. In this paper we present a powerful bidding engine which is based on a k-nearest neighbor algorithm.

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