| SDRL: interpretable and data-efficient deep reinforcement learning leveraging symbolic planning D Lyu, F Yang, B Liu, S Gustafson Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 2970-2977, 2019 | 226 | 2019 |
| Peorl: Integrating symbolic planning and hierarchical reinforcement learning for robust decision-making F Yang, D Lyu, B Liu, S Gustafson arXiv preprint arXiv:1804.07779, 2018 | 183 | 2018 |
| Bwibots: A platform for bridging the gap between ai and human–robot interaction research P Khandelwal, S Zhang, J Sinapov, M Leonetti, J Thomason, F Yang, ... The International Journal of Robotics Research 36 (5-7), 635-659, 2017 | 165 | 2017 |
| Action Language BC: Preliminary Report J Lee, V Lifschitz, F Yang The 23rd International Joint Conference on Artificial Intelligence (IJCAI'2013), 2013 | 101 | 2013 |
| A survey of revision approaches in description logics G Qi, F Yang The 2nd International Conference on Web Reasoning and Rule Systems (RR'2008 …, 2008 | 61 | 2008 |
| Task-motion planning with reinforcement learning for adaptable mobile service robots Y Jiang, F Yang, S Zhang, P Stone 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2019 | 53 | 2019 |
| Planning in action language BC while learning action costs for mobile robots P Khandelwal, F Yang, M Leonetti, V Lifschitz, P Stone The 24th International Conference on Automated Planning and Scheduling …, 2014 | 51 | 2014 |
| Planning with Task-Oriented Knowledge Acquisition for a Service Robot. K Chen, F Yang, X Chen IJCAI, 812-818, 2016 | 36 | 2016 |
| Mobile Robot Planning using Action Language BC with an Abstraction Hierarchy S Zhang, F Yang, P Khandelwal, P Stone 13th International Conference on Logic Programming and Non-monotonic …, 2015 | 34 | 2015 |
| Planning in Answer Set Programming while Learning Action Costs for Mobile Robots. F Yang, P Khandelwal, M Leonetti, P Stone AAAI Spring Symposia, 2014 | 32 | 2014 |
| Tdm: trustworthy decision-making via interpretability enhancement D Lyu, F Yang, H Kwon, W Dong, L Yilmaz, B Liu IEEE Transactions on Emerging Topics in Computational Intelligence 6 (3 …, 2021 | 28 | 2021 |
| The Semantics of Gringo and Infinitary Propositional Formulas. AJ Harrison, V Lifschitz, F Yang KR, 2014 | 28 | 2014 |
| Ontology based object categorization for robots B Johnston, F Yang, R Mendoza, X Chen, MA Williams The 7th International Conference on Practical Aspects of Knowledge …, 2008 | 26 | 2008 |
| Representing first-order causal theories by logic programs P Ferraris, J Lee, Y Lierler, V Lifschitz, F Yang Theory and Practice of Logic Programming 12 (3), 383-412, 2012 | 23 | 2012 |
| Eliminating function symbols from a nonmonotonic causal theory V Lifschitz, F Yang Knowing, Reasoning, and Acting: Essays in Honour of Hector J. Levesque …, 2011 | 16 | 2011 |
| Integrating task-motion planning with reinforcement learning for robust decision making in mobile robots Y Jiang, F Yang, S Zhang, P Stone arXiv preprint arXiv:1811.08955, 2018 | 13 | 2018 |
| Lloyd-Topor completion and general stable models V Lifschitz, F Yang Theory and Practice of Logic Programming 13 (4-5), 503-515, 2013 | 12 | 2013 |
| OBOC: Ontology based object categorisation for robots R Mendoza, B Johnston, F Yang, Z Huang, X Chen, MA Williams The 4th International Conference on Computational Intelligence, Robotics and …, 2007 | 12 | 2007 |
| Representing synonymity in causal logic and in logic programming J Lee, Y Lierler, V Lifschitz, F Yang 13th International Workshop on Non-Monotonic Reasoning (NMR'2010), 2010 | 8 | 2010 |
| Program search for machine learning pipelines leveraging symbolic planning and reinforcement learning F Yang, S Gustafson, A Elkholy, D Lyu, B Liu Genetic Programming Theory and Practice XVI, 209-231, 2019 | 7 | 2019 |
Vladimir LifschitzUniversity of Texas at AustinVerified email at cs.utexas.edu
