Universal intelligence: A definition of machine intelligence

Date

2007

Authors

Legg, Shane
Hutter, Marcus

Journal Title

Journal ISSN

Volume Title

Publisher

Springer

Abstract

A 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 equation formally captures the concept of machine intelligence in the broadest reasonable sense. We then show how this formal definition is related to the theory of universal optimal learning agents. Finally, we survey the many other tests and definitions of intelligence that have been proposed for machines.

Description

Keywords

Keywords: Computational complexity; Expert systems; Intelligent systems; Learning systems; Artificial systems; Complexity theory; Intelligence tests; Theoretical foundations; Problem solving AIXI; Complexity theory; Definitions; Intelligence; Intelligence tests; Measures; Theoretical foundations; Turing test

Citation

Source

Minds and Machines: journal for artificial intelligence, philosophy and cognitive sciences

Type

Journal article

Book Title

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Access Statement

License Rights

DOI

10.1007/s11023-007-9079-x

Restricted until

2037-12-31