| Using reward machines for high-level task specification and decomposition in reinforcement learning RT Icarte, T Klassen, R Valenzano, S McIlraith International Conference on Machine Learning, 2107-2116, 2018 | 145 | 2018 |
| LTL and Beyond: Formal Languages for Reward Function Specification in Reinforcement Learning. A Camacho, RT Icarte, TQ Klassen, RA Valenzano, SA McIlraith IJCAI 19, 6065-6073, 2019 | 115 | 2019 |
| Evaluating state-space abstractions in extensive-form games M Johanson, N Burch, R Valenzano, M Bowling Proceedings of the 2013 international conference on Autonomous agents and …, 2013 | 90 | 2013 |
| Teaching multiple tasks to an RL agent using LTL R Toro Icarte, TQ Klassen, R Valenzano, SA McIlraith Proceedings of the 17th International Conference on Autonomous Agents and …, 2018 | 89 | 2018 |
| Learning reward machines for partially observable reinforcement learning R Toro Icarte, E Waldie, T Klassen, R Valenzano, M Castro, S McIlraith Advances in neural information processing systems 32, 2019 | 63 | 2019 |
| Simultaneously searching with multiple settings: An alternative to parameter tuning for suboptimal single-agent search algorithms RA Valenzano, N Sturtevant, J Schaeffer, K Buro, A Kishimoto Twentieth International Conference on Automated Planning and Scheduling, 2010 | 60 | 2010 |
| Arvandherd: Parallel planning with a portfolio R Valenzano, H Nakhost, M Müller, J Schaeffer, N Sturtevant ECAI 2012, 786-791, 2012 | 45 | 2012 |
| A comparison of knowledge-based GBFS enhancements and knowledge-free exploration RA Valenzano, NR Sturtevant, J Schaeffer, F Xie Twenty-Fourth International Conference on Automated Planning and Scheduling, 2014 | 44 | 2014 |
| Reward machines: Exploiting reward function structure in reinforcement learning RT Icarte, TQ Klassen, R Valenzano, SA McIlraith Journal of Artificial Intelligence Research 73, 173-208, 2022 | 33 | 2022 |
| Advice-based exploration in model-based reinforcement learning R Toro Icarte, TQ Klassen, RA Valenzano, SA McIlraith Canadian Conference on Artificial Intelligence, 72-83, 2018 | 22 | 2018 |
| Using alternative suboptimality bounds in heuristic search R Valenzano, SJ Arfaee, J Thayer, R Stern, N Sturtevant Proceedings of the International Conference on Automated Planning and …, 2013 | 21 | 2013 |
| Arvand: the art of random walks H Nakhost, M Müller, R Valenzano, F Xie The, 15-16, 2011 | 20 | 2011 |
| On the completeness of best-first search variants that use random exploration RA Valenzano, F Xie Thirtieth AAAI Conference on Artificial Intelligence, 2016 | 12 | 2016 |
| Better time constrained search via randomization and postprocessing F Xie, R Valenzano, M Müller Proceedings of the International Conference on Automated Planning and …, 2013 | 11 | 2013 |
| Worst-case solution quality analysis when not re-expanding nodes in best-first search R Valenzano, N Sturtevant, J Schaeffer Proceedings of the AAAI Conference on Artificial Intelligence 28 (1), 2014 | 9 | 2014 |
| Arvandherd 2014 R Valenzano, H Nakhost, M Müller, J Schaeffer, N Sturtevant The Eighth International Planning Competition. Description of Participant …, 2014 | 8 | 2014 |
| Searching for Markovian subproblems to address partially observable reinforcement learning RT Icarte, E Waldie, TQ Klassen, R Valenzano, MP Castro, SA McIlraith Proceedings of the 4th Multi-disciplinary Conference on Reinforcement …, 2019 | 6 | 2019 |
| Probably bounded suboptimal heuristic search R Stern, G Dreiman, R Valenzano Artificial Intelligence 267, 39-57, 2019 | 5 | 2019 |
| Using advice in model-based reinforcement learning RT Icarte, TQ Klassen, R Valenzano, SA McIlraith Reinforcement Learning and Decision Making (RLDM), 2017 | 4 | 2017 |
| Using metric temporal logic to specify scheduling problems R Luo, RA Valenzano, Y Li, JC Beck, SA McIlraith Fifteenth International Conference on the Principles of Knowledge …, 2016 | 4 | 2016 |
Sheila McIlraithProfessor of Computer Science, University of Torontocs.toronto.edu의 이메일 확인됨
