{"type":"ScholarlyArticle","title":"Integrating Neurosymbolic AI in Advanced Air Mobility: A Comprehensive Survey","authors":[{"name":"Kamal Acharya","slug":"kamal-acharya","given":"Kamal","family":"Acharya","affiliation":""},{"name":"Iman Sharifi","slug":"iman-sharifi","given":"Iman","family":"Sharifi","affiliation":""},{"name":"Mehul Lad","slug":"mehul-lad","given":"Mehul","family":"Lad","affiliation":""},{"name":"Liang Sun","slug":"liang-sun","given":"Liang","family":"Sun","affiliation":""},{"name":"Houbing Song","slug":"houbing-song","given":"Houbing","family":"Song","affiliation":""}],"abstract":"Neurosymbolic AI combines neural network adaptability with symbolic reasoning, promising an approach to address the complex regulatory, operational, and safety challenges in Advanced Air Mobility (AAM). This survey reviews its applications across key AAM domains such as demand forecasting, aircraft design, and real-time air traffic management. Our analysis reveals a fragmented research landscape where methodologies, including Neurosymbolic Reinforcement Learning, have shown potential for dynamic optimization but still face hurdles in scalability, robustness, and compliance with aviation standards. We classify current advancements, present relevant case studies, and outline future research directions aimed at integrating these approaches into reliable, transparent AAM systems. By linking advanced AI techniques with AAM’s operational demands, this work provides a concise roadmap for researchers and practitioners developing next-generation air mobility solutions.","doi":"10.24963/ijcai.2025/1151","url":"https://ijcai.org/proceedings/2025/1151","pdf":"https://ijcai.org/proceedings/2025/1151.pdf","markdown":"https://ijcai.org/proceedings/2025/1151.md","bibtex":"https://ijcai.org/proceedings/2025/bibtex/1151","volume":{"slug":"2025","title":"Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2025","url":"https://ijcai.org/proceedings/2025/","year":2025,"location":"Montreal, Canada","dates":"16-22 August 2025","editors":"James Kwok","isbn":"978-1-956792-06-5","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2025"},"section":"Survey Track","track":"Survey Track","number":1151,"pages":{"first":10362,"last":10370},"keywords":["Machine Learning: ML: Applications","Machine Learning: ML: Knowledge-aided learning","Multidisciplinary Topics and Applications: MTA: Transportation","Multidisciplinary Topics and Applications: General","Machine Learning: ML: Neuro-symbolic methods"],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}