Abstract
If it is true that good problems produce good science, then it will be worthwhile to identify good problems, and even more worthwhile to discover the attributes that make them good problems. This discovery process is necessarily empirical, so we examine several challenge problems, beginning with Turing's famous test, and more than a dozen attributes that challenge problems might have. We are led to a contrast between research strategies - the successful "divide and conquer" strategy and the promising but largely untested "developmental" strategy - and we conclude that good challenge problems encourage the latter strategy.
Original language | English (US) |
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Pages (from-to) | 61-67 |
Number of pages | 7 |
Journal | AI Magazine |
Volume | 26 |
Issue number | 4 |
State | Published - Dec 2005 |
Externally published | Yes |
ASJC Scopus subject areas
- Artificial Intelligence