Discovery system (artificial intelligence)

A discovery system is an artificial intelligence system that attempts to discover new scientific concepts or laws.^[1]^[2]

Notable discovery systems have included:

Autoclass was a Bayesian Classification System written in 1986^[3]
Automated Mathematician was one of the earliest successful discovery systems. It was written in 1977 and worked by generating a modifying small Lisp programs
Eurisko was a Sequel to Automated Mathematician written in 1984
Dalton is a still maintained program capable of calculating various molecular properties initially launched in 1983 and available in open source since 2017
Glauber is a scientific discovery method written in the context of computational philosophy of science launched in 1983

References

^ Shen, Wei-Min (1990). "Functional transformations in AI discovery systems". Artificial Intelligence. 41 (3). Elsevier BV: 257–272. doi:10.1016/0004-3702(90)90045-2. ISSN 0004-3702.
^ Gil, Yolanda; Greaves, Mark; Hendler, James; Hirsh, Haym (2014-10-10). "Amplify scientific discovery with artificial intelligence". Science. 346 (6206). American Association for the Advancement of Science (AAAS): 171–172. doi:10.1126/science.1259439. ISSN 0036-8075.
^ Cheeseman, PETER; Kelly, JAMES; Self, MATTHEW; Stutz, JOHN; Taylor, WILL; Freeman, DON (1988-01-01), Laird, John (ed.), "AutoClass: A Bayesian Classification System", Machine Learning Proceedings 1988, San Francisco (CA): Morgan Kaufmann, pp. 54–64, doi:10.1016/b978-0-934613-64-4.50011-6, ISBN 978-0-934613-64-4, retrieved 2022-07-24

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