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Leslie Kaelbling - Publications

Affiliations: 
Massachusetts Institute of Technology, Cambridge, MA, United States 
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34 high-probability publications. We are testing a new system for linking publications to authors. You can help! If you notice any inaccuracies, please sign in and mark papers as correct or incorrect matches. If you identify any major omissions or other inaccuracies in the publication list, please let us know.

Year Citation  Score
2019 Amato C, Konidaris G, Kaelbling LP, How JP. Modeling and Planning with Macro-Actions in Decentralized POMDPs. The Journal of Artificial Intelligence Research. 64: 817-859. PMID 31656393 DOI: 10.1613/Jair.1.11418  0.469
2018 Konidaris G, Kaelbling LP, Lozano-Perez T. From Skills to Symbols: Learning Symbolic Representations for Abstract High-Level Planning Journal of Artificial Intelligence Research. 61: 215-289. DOI: 10.1613/Jair.5575  0.366
2015 Garrett CR, Lozano-Pérez T, Kaelbling LP. Backward-forward search for manipulation planning Ieee International Conference On Intelligent Robots and Systems. 2015: 6366-6373. DOI: 10.1109/IROS.2015.7354287  0.317
2015 Amato C, Konidaris G, Cruz G, Maynor CA, How JP, Kaelbling LP. Planning for decentralized control of multiple robots under uncertainty Proceedings - Ieee International Conference On Robotics and Automation. 2015: 1241-1248. DOI: 10.1109/ICRA.2015.7139350  0.356
2015 Amato C, Konidaris G, Omidshafiei S, Agha-Mohammadi AA, How JP, Kaelbling LP. Probabilistic planning for decentralized multi-robot systems Aaai Fall Symposium - Technical Report. 10-12.  0.314
2015 Konidaris G, Kaelbling LP, Lozano-Perez T. Symbol acquisition for probabilistic high-level planning Ijcai International Joint Conference On Artificial Intelligence. 2015: 3619-3627.  0.392
2014 Konidaris G, Kaelbling LP, Lozano-Perez T. Constructing symbolic representations for high-level planning Proceedings of the National Conference On Artificial Intelligence. 3: 1932-1938B.  0.41
2013 Kaelbling LP, Lozano-Pérez T. Integrated task and motion planning in belief space International Journal of Robotics Research. 32: 1194-1227. DOI: 10.1177/0278364913484072  0.322
2013 Levihn M, Kaelbling LP, Lozano-Perez T, Stilman M. Foresight and reconsideration in hierarchical planning and execution Ieee International Conference On Intelligent Robots and Systems. 224-231. DOI: 10.1109/IROS.2013.6696357  0.306
2013 Hadfield-Menell D, Kaelbling LP, Lozano-Perez T. Optimization in the now: Dynamic peephole optimization for hierarchical planning Proceedings - Ieee International Conference On Robotics and Automation. 4560-4567. DOI: 10.1109/ICRA.2013.6631225  0.362
2013 Konidaris G, Kaelbling LP, Lozano-Perez T. Symbol acquisition for task-level planning Aaai Workshop - Technical Report. 9-15.  0.37
2012 Kaelbling LP, Lozano-Pérez T. Unifying perception, estimation and action for mobile manipulation via belief space planning Proceedings - Ieee International Conference On Robotics and Automation. 2952-2959. DOI: 10.1109/ICRA.2012.6225237  0.323
2012 Platt R, Kaelbling L, Lozano-Perez T, Tedrake R. Non-Gaussian belief space planning: Correctness and complexity Proceedings - Ieee International Conference On Robotics and Automation. 4711-4717. DOI: 10.1109/ICRA.2012.6225223  0.308
2012 Macindoe O, Kaelbling LP, Lozano-Pérez T. POMCoP: Belief space planning for sidekicks in cooperative games Proceedings of the 8th Aaai Conference On Artificial Intelligence and Interactive Digital Entertainment, Aiide 2012. 38-43.  0.34
2012 Oliehoek FA, Witwicki SJ, Kaelbling LP. Influence-based abstraction for multiagent systems Proceedings of the National Conference On Artificial Intelligence. 2: 1422-1428.  0.428
2012 Witwicki SJ, Oliehoek FA, Kaelbling LP. Heuristic search of multiagent influence space 11th International Conference On Autonomous Agents and Multiagent Systems 2012, Aamas 2012: Innovative Applications Track. 1: 200-207.  0.313
2012 Macindoe O, Kaelbling LP, Lozano-Perez T. Assistant agents for sequential planning problems Aaai Workshop - Technical Report. 27-30.  0.416
2010 Aha DW, Boddy M, Bulitko V, D'Avila Garcez AS, Doshi P, Edelkamp S, Geib C, Gmytrasiewicz P, Goldman RP, Halevy A, Hitzler P, Isbell C, Josyula D, Kaelbling LP, Kersting K, et al. Reports of the AAAI 2010 conference workshops Ai Magazine. 31: 95-104. DOI: 10.1609/Aimag.V31I4.2318  0.378
2009 Zettlemoyer LS, Milch B, Kaelbling LP. Multi-agent filtering with infinitely nested beliefs Advances in Neural Information Processing Systems 21 - Proceedings of the 2008 Conference. 1905-1912.  0.37
2007 Pasula HM, Zettlemoyer LS, Kaelbling LP. Learning symbolic models of stochastic domains Journal of Artificial Intelligence Research. 29: 309-352. DOI: 10.1613/Jair.2113  0.373
2007 Zarybnisky E, Armacost A, Kolitz S, Barnhart C, Kaelbling L. Allocation of air resources against an intelligent adversary Collection of Technical Papers - 2007 Aiaa Infotech At Aerospace Conference. 1: 918-947.  0.312
2007 Gardiol NH, Kaelbling LP. Action-space partitioning for planning Proceedings of the National Conference On Artificial Intelligence. 2: 980-986.  0.323
2004 Gardiol NH, Kaelbling LP. Envelope-based planning in relational MDPs Advances in Neural Information Processing Systems.  0.362
2004 Chang YH, Ho T, Kaelbling LP. All learning is local: Multi-agent learning in global reward games Advances in Neural Information Processing Systems.  0.3
2004 Pasula HM, Zettlemoyer LS, Kaelbling LP. Learning probabilistic relational planning rules Proceedings of the 14th International Conference On Automated Planning and Scheduling, Icaps 2004. 73-81.  0.308
2002 Shatkay H, Kaelbling LP. Learning geometrically-constrained Hidden Markov models for robot navigation: Bridging the topological-geometrical gap Journal of Artificial Intelligence Research. 16: 167-207.  0.324
1998 Kaelbling LP, Littman ML, Cassandra AR. Planning and acting in partially observable stochastic domains Artificial Intelligence. 101: 99-134. DOI: 10.1016/S0004-3702(98)00023-X  0.546
1996 Kaelbling LP, Littman ML, Moore AW. Reinforcement learning: A survey Journal of Artificial Intelligence Research. 4: 237-285. DOI: 10.1613/Jair.301  0.496
1996 Kaelbling LP, Littman ML, Cassandra AR. Partially observable Markov decision processes for artificial intelligencea Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 1093: 146-163. DOI: 10.1007/BFb0013957  0.527
1995 Rosenschein SJ, Kaelbling LP. A situated view of representation and control Artificial Intelligence. 73: 149-173. DOI: 10.1016/0004-3702(94)00056-7  0.581
1995 Basye K, Dean T, Kaelbling LP. Learning dynamics: system identification for perceptually challenged agents Artificial Intelligence. 72: 139-171. DOI: 10.1016/0004-3702(94)00023-T  0.365
1991 Kaelbling LP. A situated-automata approach to the design of embedded agents Acm Sigart Bulletin. 2: 85-88. DOI: 10.1145/122344.122361  0.406
1991 Kaelbling LP. Foundations of learning in autonomous agents Robotics and Autonomous Systems. 8: 131-144. DOI: 10.1016/0921-8890(91)90018-G  0.373
1990 Kaelbling LP, Rosenschein SJ. Action and planning in embedded agents Robotics and Autonomous Systems. 6: 35-48. DOI: 10.1016/S0921-8890(05)80027-2  0.584
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