| Learning numerical action models from noisy and partially observable states by means of inductive rule learning techniques JA Segura-Muros, R Pérez, J Fernández-Olivares KEPS 2018 46, 2018 | 19 | 2018 |
| Integration of an automated hierarchical task planner in ros using behaviour trees JÁ Segura-Muros, J Fernández-Olivares 2017 6th International Conference on Space Mission Challenges for …, 2017 | 14 | 2017 |
| Discovering relational and numerical expressions from plan traces for learning action models JÁ Segura-Muros, R Pérez, J Fernández-Olivares Applied Intelligence 51 (11), 7973-7989, 2021 | 9 | 2021 |
| Learning HTN Domains Using Process Mining and Data Mining Techniques JA Segura-Muros, R Pérez, J Fernández-Olivares ICAPS Workshop on Generalized Planning. Pittsburgh, United States, 2017 | 6 | 2017 |
| Learning Numerical Action Models from Noisy Input Data JÁ Segura-Muros, J Fernández-Olivares, R Pérez arXiv preprint arXiv:2111.04997, 2021 | 2 | 2021 |
| Using Inductive Rule Learning Techniques to Learn Planning Domains JÁ Segura-Muros, R Pérez, J Fernández-Olivares International Conference on Information Processing and Management of …, 2018 | 1 | 2018 |
| Learning expressive numerical planning domains by integrating machine learning techniques JÁ Segura Muros Universidad de Granada, 2022 | | 2022 |
| Learning Planning Action Models with Numerical Information and Logic Relationships Using Classification Techniques JÁ Segura-Muros, R Pérez, J Fernández-Olivares Conference of the Spanish Association for Artificial Intelligence, 372-382, 2018 | | 2018 |
Juan Fdez-OlivaresAssociate Professor of Computer Science, University of GranadaAdresse e-mail validée de decsai.ugr.es
