HackerPapers

arXiv:cs/0605024cs.AI

A Formal Measure of Machine Intelligence

Shane Legg, Marcus Hutter

Early discovery. Linked by one identifiable commenter. This paper is outside the main ranking; a mention is not an endorsement.

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 measure formally captures the concept of machine intelligence in the broadest reasonable sense.

arXiv comments
8 two-column pages
Journal reference
Proc. 15th Annual Machine Learning Conference of {B}elgium and The Netherlands (Benelearn 2006) pages 73-80
DOI
Subjects
cs.AIArtificial Intelligence cs.LGMachine Learning

On Hacker News

Linked by 1 identifiable commenter in 1 comment across 1 thread, from Jan 2023 to Jan 2023.

Comments linking this paper, per year.

Discussed in comments1 thread

  1. What Is AGI-Hard 1 comment
    • https://arxiv.org/abs/cs/0605024 gives a formal model of intelligence (achieving high reward in an agent/environment setup, across all computable environments weighted by their Kolmogorov complexity) https://arxiv.org/abs/1109.5951 gives a computable approximation (dubbed AIQ…

      chriswarboView on HNParent context

Submitted to Hacker News

Connected through shared HN threads, not inferred similarity or a recommendation.