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Items where contributor is "Keller, Thomas"

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2019

Coles, Amanda and Coles, Andrew and Martínez, Moisés and Savas, Emre and Keller, Thomas and Pommerening, Florian and Helmert, Malte. (2019) On-board Planning for Robotic Space Missions using Temporal PDDL. In: Proceedings of the 11th International Workshop on Planning and Scheduling for Space (IWPSS). pp. 1-9.

Geißer, Florian and Speck, David and Keller, Thomas. (2019) An Analysis of the Probabilistic Track of the IPC 2018. In: Proceedings of the 2019 Workshop on the International Planning Competition. pp. 27-35.

Cui, Hao and Keller, Thomas and Khardon, Roni. (2019) Stochastic Planning with Lifted Symbolic Trajectory Optimization. In: Proceedings of the 29th International Conference on Automated Planning and Scheduling. pp. 119-127.

2018

Heusner, Manuel and Keller, Thomas and Helmert, Malte. (2018) Best-Case and Worst-Case Behavior of Greedy Best-First Search. In: Proceedings of the 27th International Joint Conference on Artificial Intelligence. pp. 1463-1470.

Heusner, Manuel and Keller, Thomas and Helmert, Malte. (2018) Search Progress and Potentially Expanded States in Greedy Best-First Search. In: Proceedings of the 27th International Joint Conference on Artificial Intelligence. pp. 5269-5273.

Ocón, Jorge and Colmenero, Francisco and Estremera, Joaquin and Buckley, Karl and Alonso, Mercedes and Heredia, Enrique and Garcia, Javier and Coles, Andrew and Coles, Amanda and Martinez Munoz, Moises and Savas, Emre and Pommerening, Florian and Keller, Thomas and Karachalios, Spyros and Woods, Mark and Dragomir, Iulia and Bensalem, Saddek and Dissaux, Pierre and Schach, Arnaud. (2018) The ERGO Framework and its Use in Planetary/Orbital Scenarios. In: Proceedings of the 69th International Astronautical Congress (IAC 2018).

2017

Seipp, Jendrik and Keller, Thomas and Helmert, Malte. (2017) Narrowing the Gap Between Saturated and Optimal Cost Partitioning for Classical Planning. In: Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI 2017). pp. 3651-3657.

Heusner, Manuel and Keller, Thomas and Helmert, Malte. (2017) Understanding the Search Behaviour of Greedy Best-First Search. In: Proceedings of the 10th Annual Symposium on Combinatorial Search (SoCS 2017). Palo Alto, California.

Paul, Gerald and Röger, Gabriele and Keller, Thomas and Helmert, Malte. (2017) Optimal Solutions to Large Logistics Planning Domain Problems. In: Proceedings of the 10th Annual Symposium on Combinatorial Search (SoCS 2017).

Seipp, Jendrik and Keller, Thomas and Helmert, Malte. (2017) A Comparison of Cost Partitioning Algorithms for Optimal Classical Planning. In: Proceedings of the 27th International Conference on Automated Planning and Scheduling (ICAPS 2017).

Ocón, Jorge and Delfa, Juan Manuel and Medina, Alberto and Lachat, Daisy and Marc, Robert and Woods, Mark and Wallace, Ian and Coles, Andrew and Coles, Amanda and Long, Derek and Keller, Thomas and Helmert, Malte and Bensalem, Saddek. (2017) ERGO: A Framework for the Development of Autonomous Robots. In: Proceedings of the 14th ESA Symposium on Advanced Space Technologies for Robotics and Automation (ASTRA 2017).

2016

Keller, Thomas and Pommerening, Florian and Seipp, Jendrik and Geißer, Florian and Mattmüller, Robert. (2016) State-dependent Cost Partitionings for Cartesian Abstractions in Classical Planning. In: Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI 2016), 4. Palo Alto, pp. 3161-3169.

Geißer, Florian and Keller, Thomas and Mattmüller , Robert. (2016) Abstractions for Planning with State-Dependent Action Costs. In: Proceedings of the Twenty-Sixth International Conference on Automated Planning and Scheduling (ICAPS 2016). pp. 140-148.

Skočaj, Danijel and Vrečko, Alen and Mahnič, Marko and Janíček, Miroslav and Kruijff, Geert-Jan and Hanheide, Marc and Hawes, Nick and Wyatt, Jeremy and Keller, Thomas and Zhou, Kai and Zillich, Michael and Kristan, Matej. (2016) An integrated system for interactive continuous learning of categorical knowledge. Journal of Experimental & Theoretical Artificial Intelligence, 28 (5). pp. 823-848.