Article Contents
COMMENTARY   Open Access     Cite

Challenges and outlook of artificial intelligence in open-ended urban environments

More Information
  • Corresponding author: liuh@ust.hk (H.L.)
  • 加载中
  • [1] Zheng Y., Hao Q., Wang J. et al. (2024). A survey of machine learning for urban decision making: Applications in planning, transportation, and healthcare. ACM Comput. Surv. 57:1−41. DOI:10.1145/3695986

    View in Article CrossRef Google Scholar

    [2] Huang J., Xu Y., Wang Q. et al. (2025). Foundation models and intelligent decision-making: Progress, challenges, and perspectives. The Innovation 6:100948. DOI:10.1016/j.xinn.2025.100948

    View in Article CrossRef Google Scholar

    [3] Wang Z., Gao Y., Yang D. et al. (2025). Reliability simulation testing and verification technologies for intelligent systems: frontiers, progress, and challenges. J. Syst. Simul. 37:1583−1606. DOI:10.16182/j.issn1004731x.joss.25-0554

    View in Article CrossRef Google Scholar

    [4] Schölkopf B. and von Kügelgen J. (2022). From statistical to causal learning. Proc. Int. Cong. Math. 7:5540-5593. DOI:10.4171/ICM2022/173

    View in Article CrossRef Google Scholar

    [5] Liu J. and Cui P. (2025). Data heterogeneity modeling for trustworthy machine learning. Proc. 31st ACM SIGKDD Conf. Knowl. Discov. Data Min. 2:6086-6095. DOI:10.1145/3711896.3736560

    View in Article CrossRef Google Scholar

    [6] Shorinwa O., Mei Z., Lidard J. et al. (2025). A survey on uncertainty quantification of large language models: Taxonomy, open research challenges, and future directions. ACM Comput. Surv. 58:1−38. DOI:10.1145/3744238

    View in Article CrossRef Google Scholar

    [7] Wang Y., Wang T. and Yue T. (2025). Uncertainty propagation from sensor data to deep learning models in autonomous driving. Inf. Softw. Technol. 183:107735. DOI:10.1016/j.infsof.2025.107735

    View in Article CrossRef Google Scholar

    [8] Zeng J., Yu C., Yang X. et al. (2025). CityLight: A neighborhood-inclusive universal model for coordinated city-scale traffic signal control. In Proc. 34th ACM Int. Conf. Inf. Knowl. Manag. 4036–4044. DOI:10.1145/3746252.3761285

    View in Article Google Scholar

    [9] Civil Aviation Administration of China, (in Chinese). https://www.caac.gov.cn/XXGK/XXGK/TJSJ/202604/t20260417_230601.html

    View in Article Google Scholar

    [10] Yuan J., Gao H., Dai D. et al. (2025). Native sparse attention: Hardware-aligned and natively trainable sparse attention. In Proc. 63rd Annu. Meeting Assoc. Comput. Linguistics (Vol. 1: Long Papers) 23078-23097. DOI:10.18653/v1/2025.acl-long.1126

    View in Article Google Scholar

  • Cite this article:

    Jiang W., Han J. and Liu H. (2026). Challenges and outlook of artificial intelligence in open-ended urban environments. AI Plus 1:100011. https://doi.org/10.59717/ipj.aiplus.2026.100011
    Jiang W., Han J. and Liu H. (2026). Challenges and outlook of artificial intelligence in open-ended urban environments. AI Plus 1:100011. https://doi.org/10.59717/ipj.aiplus.2026.100011

Welcome!

To request copyright permission to republish or share portions of our works, please visit Copyright Clearance Center's (CCC) Marketplace website at marketplace.copyright.com.

Figures(1)    

Share

  • Share the QR code with wechat scanning code to friends and circle of friends.

Article Metrics

Article views(53) PDF downloads(16)

Relative Articles

Cited by

Catalog

    /

    DownLoad:  Full-Size Img  PowerPoint