Publications

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J
Jiménez, S., Fernández, F., and Borrajo, D., Integrating Planning, Execution, and Learning to Improve Plan Execution, Computational Intelligence, vol. 29, 2013, pp. 1–36.
Jiménez, S., Jonsson, A., and Palacios, H., Temporal Planning With Required Concurrency Using Classical Planning, Proceedings of the 25th International Conference on Automated Planning and Scheduling (ICAPS'15), 2015.
Jiménez, S., and Jonsson, A., Computing Plans with Control Flow and Procedures using a Classical Planner, Proceedings of the 8th International Annual Symposium on Combinatorial Search (SoCS'15), 2015.
Jiménez, S., Fernández, F., and Borrajo, D., Machine Learning of Plan Robustness Knowledge About Instances, Machine Learning: {ECML} 2005, 16th European Conference on Machine Learning, Porto, Portugal, October 3-7, 2005, Proceedings, 2005, pp. 609–616.
Jonsson, A., The Role of Macros in Tractable Planning Over Causal Graphs, Proceedings of the 20th International Joint Conference on Artificial Intelligence (IJCAI'07), 2007, pp. 1936-1941.
Jonsson, A., The Role of Macros in Tractable Planning, Journal of Artificial Intelligence Research, vol. 36, 2009, pp. 471-511.
Jonsson, A., and Barto, A., Automated State Abstraction for Options using the U-Tree Algorithm, Advances in Neural Information Processing Systems (NIPS'00), 2001, pp. 1054-1060.
Jonsson, A., and Barto, A., Active Learning of Dynamic Bayesian Networks in Markov Decision Processes, Lecture Notes in Artificial Intelligence: Abstraction, Reformulation, and Approximation (SARA'07), 2007, pp. 273-284.
Jonsson, A., Parisot, C., and De Vleeschouwer, C., A Learning Approach to Interactive Browsing of Surveillance Content, Proceedings of the 4th International Conference on Distributed Smart Cameras (ICDSC'10), 2010.
Jonsson, A., Johns, J., Mehranian, H., Arroyo, I., Woolf, B., Barto, A., Fisher, D., and Mahadevan, S., Evaluating the Feasibility of Learning Student Models from Data, Proceedings of the Workshop on Educational Data Mining at AAAI'05, 2005, pp. 1-6.
Jonsson, A., Jonsson, P., and Lööw, T., When Acyclicity Is Not Enough: Limitations of the Causal Graph, Proceedings of the 23rd International Conference on Automated Planning and Scheduling (ICAPS'13), 2013.
Jonsson, A., Efficient Pruning of Operators in Planning Domains, Lecture Notes in Artificial Intelligence: Current Topics in Artificial Intelligence (CAEPIA'07), 2007, pp. 130-139.
Jonsson, A., and Barto, A., Causal Graph Based Decomposition of Factored MDPs, Journal of Machine Learning Research, vol. 7, 2006, pp. 2259-2301.
Jonsson, A., and Rovatsos, M., Scaling Up Multiagent Planning: A Best-Response Approach, Proceedings of the 21st International Conference on Automated Planning and Scheduling (ICAPS'11), 2011.
Jonsson, A., Jonsson, P., and Lööw, T., Limitations of Acyclic Causal Graphs for Planning, Artificial Intelligence, vol. 210, 2014, pp. 36-55.
Jonsson, A., and Barto, A., A Causal Approach to Hierarchical Decomposition of Factored MDPs, Proceedings of the 22nd International Conference on Machine Learning (ICML'05), 2005, pp. 401-408.
Jonsson, A., and Gómez, V., Hierarchical Linearly-Solvable Markov Decision Problems, Proceedings of the 26th International Conference on Automated Planning and Scheduling (ICAPS'16), 2016.
K
Keyder, E., and Geffner, H., Heuristics for Planning with Action Costs Revisited, Proc. of European Conf. on Artificial Intelligence (ECAI-08), 2008, pp. 588–592.
Keyder, E., and Geffner, H., Set-Additive and TSP Heuristics for Planning with Action Costs and Soft Goals, Workshop on Heuristics for Domain-Independent Planning (ICAPS'07), 2007.
Klaus, J., Miesenberger, K., Zagler, W. L., and Burger, D., Computers Helping People with Special Needs, 9th International Conference, ICCHP 2004, Paris, France, July 7-9, 2004, Proceedings, Lecture Notes in Computer Science, vol. 3118, 2004.
Kocák, T., Neu, G., and Valko, M., Online learning with Erdős-Rényi side-observation graphs, Uncertainty in Artificial Intelligence, 2016, pp. 339–347.
Kocák, T. \vs, Neu, G., Valko, M., and Munos, R., Efficient learning by implicit exploration in bandit problems with side observations, Advances in Neural Information Processing Systems 27 (NIPS), 2014, pp. 613-621.
Kocák, T., Neu, G., and Valko, M., Online learning with noisy side observations, International Conference on Artificial Intelligence and Statistics, 2016, pp. 1186–1194.
Kolobov, A., Mausam, M., Weld, D. S., and Geffner, H., Heuristic search for generalized stochastic shortest path MDPs, Twenty-First International Conference on Automated Planning and Scheduling, 2011.
Kominis, F., and Geffner, H., Multiagent Online Planning with Nested Beliefs and Dialogue, Proceedings of the 27th International Conference on Automated Planning and Scheduling (ICAPS'17), 2017.

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