{"type":"ScholarlyArticle","title":"Application of Neurosymbolic AI to Sequential Decision Making","authors":[{"name":"Carlos Núñez-Molina","slug":"carlos-nunez-molina","given":"Carlos","family":"Núñez-Molina","affiliation":"Universidad de Granada , Spain"}],"abstract":"In the history of AI, two main paradigms have been proposed to solve Sequential Decision Making (SDM) problems: Automated Planning (AP) and Reinforcement Learning (RL). Among the many proposals to unify both fields, the one known as neurosymbolic AI has recently attracted great attention. It combines the Deep Neural Networks used in modern RL with the symbolic representations typical of AP. The main goal of this PhD is to progress the state of the art in neurosymbolic AI for SDM, developing methods for both solving these problems and learning aspects of their structure.","doi":"10.24963/ijcai.2022/834","url":"https://ijcai.org/proceedings/2022/834","pdf":"https://ijcai.org/proceedings/2022/0834.pdf","markdown":"https://ijcai.org/proceedings/2022/834.md","bibtex":"https://ijcai.org/proceedings/2022/bibtex/834","volume":{"slug":"2022","title":"Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2022","url":"https://ijcai.org/proceedings/2022/","year":2022,"location":"Vienna","dates":"23-29 July 2022","editors":"Luc De Raedt","isbn":"978-1-956792-00-3","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2022"},"section":"Doctoral Consortium","track":"Doctoral Consortium","number":834,"pages":{"first":5863,"last":5864},"keywords":["Machine Learning (ML): General","Planning, Routing, and Scheduling (PRS): General","Knowledge Representation and Reasoning (KRR): General"],"videos":[],"references":[{"position":1,"raw":"[Bonanno et al., 2016] David Bonanno, Mark Roberts, Leslie Smith, and David W Aha. Selecting subgoals using deep learning in minecraft: A preliminary report. In IJCAI Workshop on Deep Learning for AI, 2016.","title":"Selecting subgoals using deep learning in minecraft: A preliminary report","authors":"David Bonanno, Mark Roberts, Leslie Smith, David W Aha","year":"2016","venue":"IJCAI Workshop on Deep Learning for AI","doi":null,"url":null,"internal_url":null},{"position":2,"raw":"[Fuentetaja and De la Rosa, 2012] Raquel Fuentetaja and Tomás De la Rosa. A planning-based approach for gener- ating planning problems. In Workshops at the Twenty-Sixth AAAI Conference on Artificial Intelligence, 2012.","title":"Raquel Fuentetaja and Tomás De la Rosa. A planning-based approach for generating planning problems","authors":"De Fuentetaja, Rosa La","year":"2012","venue":"Workshops at the Twenty-Sixth AAAI Conference on Artificial Intelligence","doi":null,"url":null,"internal_url":null},{"position":3,"raw":"[Jaidee et al., 2012] Ulit Jaidee, Héctor Munoz-Avila, and David W Aha. Learning and reusing goal-specific policies for goal-driven autonomy. In ICCBR, 2012.","title":"Learning and reusing goal-specific policies for goal-driven autonomy","authors":"Ulit Jaidee, Héctor Munoz-Avila, David W Aha","year":"2012","venue":"ICCBR","doi":null,"url":null,"internal_url":null},{"position":4,"raw":"[Lotinac and Jonsson, 2016] Damir Lotinac and Anders Jon- sson. Constructing hierarchical task models using invari- ance analysis. In ECAI. 2016.","title":"Damir Lotinac and Anders Jonsson. Constructing hierarchical task models using invariance analysis","authors":"Jonsson Lotinac","year":"2016","venue":"ECAI","doi":null,"url":null,"internal_url":null},{"position":5,"raw":"[Núñez-Molina et al., 2022] Carlos Núñez-Molina, Juan Fdez-Olivares, and Raúl Pérez. Learning to select goals in automated planning with deep q-learning. Expert Syst. Appl., 2022. In Press.","title":"Learning to select goals in automated planning with deep q-learning","authors":"Carlos Núñez-Molina, Juan Fdez-Olivares, Raúl Pérez","year":"2022","venue":"Expert Syst. Appl","doi":null,"url":null,"internal_url":null},{"position":6,"raw":"[You et al., 2018] Jiaxuan You, Bowen Liu, Zhitao Ying, Vi- jay Pande, and Jure Leskovec. Graph convolutional pol- icy network for goal-directed molecular graph generation. NeurIPS, 2018.","title":"Graph convolutional policy network for goal-directed molecular graph generation","authors":"Jiaxuan You, Bowen Liu, Zhitao Ying, Vijay Pande, Jure Leskovec","year":"2018","venue":"NeurIPS","doi":null,"url":null,"internal_url":null}],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}