The Computational Gauntlet of Human-Like Learning
| Autor: | Pat Langley |
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| Rok vydání: | 2022 |
| Předmět: | |
| Zdroj: | Proceedings of the AAAI Conference on Artificial Intelligence. 36:12268-12273 |
| ISSN: | 2374-3468 2159-5399 |
| DOI: | 10.1609/aaai.v36i11.21489 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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