Kamal Acharya

Ph.D. Candidate at UMBC, AI Researcher

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Conference Paper

Integrating neurosymbolic AI in advanced air mobility: a comprehensive survey

2025 IJCAI 2025 DOI: 10.24963/ijcai.2025/1151

Neurosymbolic AI Advanced Air Mobility Survey

DOI Publisher Page Cite

Abstract

This survey examines how neurosymbolic AI can support Advanced Air Mobility systems by combining neural adaptability with symbolic reasoning. It reviews applications across demand forecasting, aircraft design, and real-time air traffic management, while discussing scalability, robustness, regulatory compliance, safety, and transparency challenges.

Plain-Language Summary

The paper explains how AI systems that both learn from data and reason with rules could help make future air mobility systems safer, more transparent, and easier to regulate.

Why This Paper Matters

This survey links advanced AI methods with the operational and safety requirements of AAM, helping researchers identify where neurosymbolic approaches can be practically useful.

Research Summary

This paper connects neurosymbolic AI with the operational needs of Advanced Air Mobility. AAM systems require adaptive decision-making, but they also operate in safety-critical and regulated environments where opaque AI decisions are difficult to trust.

The survey reviews how neural learning and symbolic reasoning can be combined across AAM domains such as demand forecasting, aircraft design, and air traffic management. It also identifies barriers around scalability, robustness, certification, and compliance.

The paper is useful because it frames neurosymbolic AI as a practical tool for making future air mobility systems more transparent and reliable, rather than only as a theoretical AI paradigm.

Key Contributions

  • Surveys neurosymbolic AI applications across major AAM domains.
  • Connects demand forecasting, aircraft design, and air traffic management with transparent AI methods.
  • Identifies scalability, robustness, and aviation-compliance barriers.
  • Provides a roadmap for reliable and explainable AI in next-generation air mobility.

Publication Details

Type
Conference Paper
Venue
IJCAI 2025
Year
2025
Pages
10362-10370

Authors

Acharya K., Sharif I., Lad M., Sun L., Song H.

Research Topics

Neurosymbolic AI Advanced Air Mobility Survey

Citation

@inproceedings{acharya2025-integrating-neurosymbolic-ai-in-advanced-air-mobility-a-comprehensive-survey,
  title = {Integrating neurosymbolic AI in advanced air mobility: a comprehensive survey},
  author = {Acharya K. and Sharif I. and Lad M. and Sun L. and Song H.},
  booktitle = {IJCAI 2025},
  year = {2025},
  doi = {10.24963/ijcai.2025/1151}
}