The Computational Gauntlet of Human-Like Learning


  • Pat Langley Institute for the Study of Learning and Expertise Stanford University Center for Design Research, Mechanical Engineering Stanford University



Machine Learning, Human Learning, Cognitive Psychology


In this paper, I pose a major challenge for AI researchers: to develop systems that learn in a human-like manner. I briefly review the history of machine learning, noting that early work made close contact with results from cognitive psychology but that this is no longer the case. I identify seven characteristics of human behavior that, if reproduced, would offer better ways to acquire expertise than statistical induction over massive training sets. I illustrate these points with two domains - mathematics and driving - where people are effective learners and review systems that address them. In closing, I suggest ways to encourage more research on human-like learning.




How to Cite

Langley, P. (2022). The Computational Gauntlet of Human-Like Learning. Proceedings of the AAAI Conference on Artificial Intelligence, 36(11), 12268-12273.