| BLOG: Probabilistic Models with Unknown Objects B Milch, B Marthi, S Russell, D Sontag, DL Ong, A Kolobov Statistical relational learning, 373, 2007 | 619 | 2007 |
| Open x-embodiment: Robotic learning datasets and rt-x models A O'Neill, A Rehman, A Gupta, A Maddukuri, A Gupta, A Padalkar, A Lee, ... arXiv preprint arXiv:2310.08864, 2023 | 262 | 2023 |
| Parallel task routing for crowdsourcing J Bragg, A Kolobov, M Mausam, D Weld Proceedings of the AAAI Conference on Human Computation and Crowdsourcing 2 …, 2014 | 222* | 2014 |
| Planning with Markov decision processes: An AI perspective Mausam, A Kolobov Synthesis Lectures on Artificial Intelligence and Machine Learning 6 (1), 1-210, 2012 | 203* | 2012 |
| Introduction to statistical relational learning D Koller, N Friedman, S Džeroski, C Sutton, A McCallum, A Pfeffer, ... MIT press, 2007 | 178 | 2007 |
| Interactive teaching strategies for agent training O Amir, E Kamar, A Kolobov, B Grosz IJCAI 2016, 2016 | 148 | 2016 |
| Heuristic search for generalized stochastic shortest path MDPs A Kolobov, Mausam, DS Weld, H Geffner Twenty-First International Conference on Automated Planning and Scheduling, 2011 | 112* | 2011 |
| Safe reinforcement learning via curriculum induction M Turchetta, A Kolobov, S Shah, A Krause, A Agarwal Advances in Neural Information Processing Systems 33, 12151-12162, 2020 | 105 | 2020 |
| A Theory of Goal-Oriented MDPs with Dead Ends A Kolobov, Mausam, DS Weld UAI, 2012 | 101* | 2012 |
| LRTDP vs. UCT for Online Probabilistic Planning A Kolobov, Mausam, DS Weld Twenty-Sixth AAAI Conference on Artificial Intelligence, 2012 | 75* | 2012 |
| Approximate inference for infinite contingent Bayesian networks B Milch, B Marthi, D Sontag, S Russell, DL Ong, A Kolobov AISTATS, 2005 | 73 | 2005 |
| Heuristic-guided reinforcement learning CA Cheng, A Kolobov, A Swaminathan Advances in Neural Information Processing Systems 34, 13550-13563, 2021 | 57 | 2021 |
| Open X-Embodiment: Robotic learning datasets and RT-X models OXE Collaboration, A O’Neill, A Rehman, A Maddukuri, A Gupta, ... arXiv preprint arXiv:2310.08864 1 (2), 2023 | 54 | 2023 |
| Reverse Iterative Deepening for Finite-Horizon MDPs with Large Branching Factors A Kolobov, P Dai, Mausam, DS Weld Proceedings of the 22nd International Conference on Automated Planning and …, 2012 | 53* | 2012 |
| Metareasoning for planning under uncertainty CH Lin, A Kolobov, E Kamar, E Horvitz arXiv preprint arXiv:1505.00399, 2015 | 46 | 2015 |
| ReTrASE: Integrating paradigms for approximate probabilistic planning A Kolobov, Mausam, DS Weld Twenty-First International Joint Conference on Artificial Intelligence, 1746 …, 2009 | 43 | 2009 |
| SixthSense: Fast and reliable recognition of dead ends in MDPs A Kolobov, Mausam, DS Weld Twenty-Fourth AAAI Conference on Artificial Intelligence, 2010 | 37* | 2010 |
| TODTLER: Two-order-deep transfer learning J Van Haaren, A Kolobov, J Davis Proceedings of the AAAI Conference on Artificial Intelligence 29 (1), 2015 | 36 | 2015 |
| Classical Planning in MDP Heuristics: With a Little Help from Generalization A Kolobov, Mausam, DS Weld Twentieth International Conference on Automated Planning and Scheduling, 97-104, 2010 | 35* | 2010 |
| Policy improvement via imitation of multiple oracles CA Cheng, A Kolobov, A Agarwal Advances in Neural Information Processing Systems 33, 5587-5598, 2020 | 30 | 2020 |
