| AlphaX: eXploring Neural Architectures with Deep Neural Networks and Monte Carlo Tree Search L Wang, Y Zhao, Y Jinnai, Y Tian, R Fonseca Proceedings of the AAAI Conference on Artificial Intelligence, 2018 | 33 | 2018 |
| Policy and value transfer in lifelong reinforcement learning D Abel*, Y Jinnai*, SY Guo, G Konidaris, M Littman International Conference on Machine Learning, 20-29, 2018 | 23 | 2018 |
| State abstraction as compression in apprenticeship learning D Abel, D Arumugam, K Asadi, Y Jinnai, ML Littman, LLS Wong Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 3134-3142, 2019 | 21 | 2019 |
| Learning to Prune Dominated Action Sequences in Online Black-box Planning Y Jinnai, A Fukunaga Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017 | 16 | 2017 |
| Abstract Zobrist Hashing: An Efficient Work Distribution Method for Parallel Best-First Search Y Jinnai, A Fukunaga Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence …, 2016 | 12 | 2016 |
| Discovering options for exploration by minimizing cover time Y Jinnai, JW Park, D Abel, G Konidaris Proceedings of the 36th International Conference on Machine Learning, 2019 | 9 | 2019 |
| Finding Options that Minimize Planning Time Y Jinnai, D Abel, DE Hershkowitz, M Littman, G Konidaris Proceedings of the 36th International Conference on Machine Learning, 2018 | 7 | 2018 |
| A Survey of Parallel A* A Fukunaga, A Botea, Y Jinnai, A Kishimoto arXiv preprint arXiv:1708.05296, 2017 | 7 | 2017 |
| Exploration in reinforcement learning with deep covering options Y Jinnai, JW Park, MC Machado, G Konidaris International Conference on Learning Representations, 2019 | 5 | 2019 |
| Automated Creation of Efficient Work Distribution Functions for Parallel Best-First Search Y Jinnai, A Fukunaga International Conference on Automated Planning and Scheduling, 2016 | 5 | 2016 |
| Parallel a* for state-space search A Fukunaga, A Botea, Y Jinnai, A Kishimoto Handbook of Parallel Constraint Reasoning, 419-455, 2018 | 3 | 2018 |
| On hash-based work distribution methods for parallel best-first search Y Jinnai, A Fukunaga Journal of Artificial Intelligence Research 60, 491-548, 2017 | 3 | 2017 |
| Lipschitz lifelong reinforcement learning E Lecarpentier, D Abel, K Asadi, Y Jinnai, E Rachelson, ML Littman arXiv preprint arXiv:2001.05411, 2020 | 2 | 2020 |
| Knossos: Compiling AI with AI Y Jinnai, A Mehrjou, K Ciosek, A Mitenkova, A Lawrence, T Ellis, ... | | 2019 |
| Skill Discovery with Well-Defined Objectives Y Jinnai, D Abel, JW Park, DE Hershkowitz, M Littman, G Konidaris Structure & Priors in Reinforcement Learning (SPiRL) at ICLR 2019, 2019 | | 2019 |
| Tiltcopter F Bystricky, Y Jinnai, F Rice | | 2018 |
| A Graph-Partitioning Based Approach for Parallel Best-First Search Y Jinnai, A Fukunaga Heuristics and Search for Domain-independent Planning (HSDIP) at ICAPS 2017, 35, 2017 | | 2017 |
| Learning to Avoid Dominated Action Sequences in Planning for Black-Box Domains Y Jinnai, A Fukunaga Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence …, 2017 | | 2017 |
| State Abstraction as Compression in Apprenticeship Learning Download PDF D Abel, D Arumugam, K Asadi, Y Jinnai, ML Littman, LLS Wong | | |
| State Abstraction as Compression in Apprenticeship Learning Supplementary Material D Abel, D Arumugam, K Asadi, Y Jinnai, ML Littman, LLS Wong a∈ A 1, 2, 0 | | |
David AbelResearch Scientist, DeepMindVerified email at google.com
