- author = "Gary Anthes",
- title = "Deep Data Dives Discover Natural Laws",
- journal = "Communications of the ACM",
- year = "2009",
- volume = "52",
- number = "11",
- pages = "13--14",
- month = nov,
- note = "News",
- keywords = "genetic algorithms, genetic programming",
- ISSN = "0001-0782",
-
URL = "
http://cacm.acm.org/magazines/2009/11/48443-deep-data-dives-discover-natural-laws/pdf",
-
DOI = "
doi:10.1145/1592761.1592768",
- size = "2 pages",
-
abstract = "Computer scientists have found a way to bootstrap
science, using evolutionary computation to find
fundamental meaning in massive amounts of raw
data.
Mining scientific data for patterns and relationships has been a common practice for decades, and the use of self-mutating genetic algorithms is nothing new, either. But now a pair of computer scientists at Cornell University have pushed these techniques into an entirely new realm, one that could fundamentally transform the methods of science at the frontiers of research.",
- notes = "Report on \cite{Science09:Schmidt}",
