Autonomous Intelligent Systems (Jun 2024)

Human feedback enhanced autonomous intelligent systems: a perspective from intelligent driving

  • Kang Yuan,
  • Yanjun Huang,
  • Lulu Guo,
  • Hong Chen,
  • Jie Chen

DOI
https://doi.org/10.1007/s43684-024-00071-z
Journal volume & issue
Vol. 4, no. 1
pp. 1 – 10

Abstract

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Abstract Artificial intelligence empowers the rapid development of autonomous intelligent systems (AISs), but it still struggles to cope with open, complex, dynamic, and uncertain environments, limiting its large-scale industrial application. Reliable human feedback provides a mechanism for aligning machine behavior with human values and holds promise as a new paradigm for the evolution and enhancement of machine intelligence. This paper analyzes the engineering insights from ChatGPT and elaborates on the evolution from traditional feedback to human feedback. Then, a unified framework for self-evolving intelligent driving (ID) based on human feedback is proposed. Finally, an application in the congested ramp scenario illustrates the effectiveness of the proposed framework.

Keywords