About: Discovery system (AI research)

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A discovery system is an artificial intelligence system that attempts to discover new scientific concepts or laws. The aim of discovery systems is to automate scientific data analysis and the scientific discovery process. Ideally, an artificial intelligence system should be able to search systematically through the space of all possible hypotheses and yield the hypothesis - or set of equally likely hypotheses - that best describes the complex patterns in data.

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rdfs:label	Discovery system (AI research) (en)
rdfs:comment	A discovery system is an artificial intelligence system that attempts to discover new scientific concepts or laws. The aim of discovery systems is to automate scientific data analysis and the scientific discovery process. Ideally, an artificial intelligence system should be able to search systematically through the space of all possible hypotheses and yield the hypothesis - or set of equally likely hypotheses - that best describes the complex patterns in data. (en)
dcterms:subject	Applications of artificial intelligence Artificial intelligence Machine learning Data mining
Wikipage page ID	66775160 (xsd:integer)
Wikipage revision ID	1100822154 (xsd:integer)
Link from a Wikipage to another Wikipage	QLattice Neural network Hod Lipson Applications of artificial intelligence Artificial intelligence Cornell University Lisp (programming language) Machine learning Glauber Dalton (program) Artificial intelligence Data mining Black box Automated Mathematician Eureqa Eurisko Expert system Symbolic regression dbr:Autoclass
Link from a Wikipage to an external page	https://royalsociety.org/-/media/policy/projects/ai-and-society/AI-revolution-in-science.pdf
sameAs	Discovery system (AI research) Discovery system (AI research)
dbp:wikiPageUsesTemplate	dbt:Reflist dbt:Short_description dbt:Math-stub dbt:Computable_knowledge dbt:AI-stub
has abstract	A discovery system is an artificial intelligence system that attempts to discover new scientific concepts or laws. The aim of discovery systems is to automate scientific data analysis and the scientific discovery process. Ideally, an artificial intelligence system should be able to search systematically through the space of all possible hypotheses and yield the hypothesis - or set of equally likely hypotheses - that best describes the complex patterns in data. During the era known as the second AI summer (approximately 1978-1987), various systems akin to the era's dominant expert systems were developed to tackle the problem of extracting scientific hypotheses from data, with or without interacting with a human scientist. These systems included , Automated Mathematician, Eurisko, which aimed at general-purpose hypothesis discovery, and more specific systems such as Dalton, which uncovers molecular properties from data. The dream of building systems that discover scientific hypotheses was pushed to the background with the second AI winter and the subsequent resurgence of subsymbolic methods such as neural networks. Subsymbolic methods emphasize prediction over explanation, and yield models which works well but are difficult or impossible to explain which has earned them the name black box AI. A black-box model cannot be considered a scientific hypothesis, and this development has even led some researchers to suggest that the traditional aim of science - to uncover hypotheses and theories about the structure of reality - is obsolete. Other researchers disagree and argue that subsymbolic methods are useful in many cases, just not for generating scientific theories. (en)
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page length (characters) of wiki page	8538 (xsd:nonNegativeInteger)
foaf:isPrimaryTopicOf	wikipedia-en:Discovery_system_(AI_research)
is Link from a Wikipage to another Wikipage of	Traveller Adventure 5: Trillion Credit Squadron Automated Mathematician Eurisko Discovery system Symbolic regression
is Wikipage disambiguates of	Discovery system
is genre of	Eurisko
is genre of	Eurisko
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