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A formal measure of machine intelligence

dc.contributor.authorLegg, Shane
dc.contributor.authorHutter, Marcus
dc.date.accessioned2015-08-31T02:20:42Z
dc.date.available2015-08-31T02:20:42Z
dc.date.issued2006-05
dc.description.abstractA fundamental problem in artificial intelligence is that nobody really knows what intelligence is. The problem is especially acute when we need to consider artificial systems which are significantly different to humans. In this paper we approach this problem in the following way: We take a number of well known informal definitions of human intelligence that have been given by experts, and extract their essential features. These are then mathematically formalised to produce a general measure of intelligence for arbitrary machines. We believe that this measure formally captures the concept of machine intelligence in the broadest reasonable sense.en_AU
dc.identifier.urihttp://hdl.handle.net/1885/15032
dc.publisherBelgian-Dutch Conference on Machine Learning (Benelearn)en_AU
dc.relation.ispartofProceedings of the 15th Annual Machine Learning Conference of Belgium and The Netherlands Benelearn'06en_AU
dc.rights© The Author(s)en_AU
dc.titleA formal measure of machine intelligenceen_AU
dc.typeConference paperen_AU
local.bibliographicCitation.lastpage80en_AU
local.bibliographicCitation.startpage73en_AU
local.contributor.affiliationHutter, M., Research School of Computer Science, The Australian National Universityen_AU
local.contributor.authoruidu4350841en_AU
local.type.statusPublished Versionen_AU

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