Year: 2011
Type: preprint
Abstract: The Universal Intelligence Measure is a recently proposed formal definition of intelligence. It is mathematically specified, extremely general, and captures the essence of many informal definitions of intelligence. It is based on Hutter's Universal Artificial Intelligence theory, an extension of Ray Solomonoff's pioneering work on universal induction. Since the Universal Intelligence Measure is only asymptotically computable, building a practical intelligence test from it is not straightforward. This paper studies the practical issues involved in developing a real-world UIM-based performance metric. Based on our investigation, we develop a prototype implementation which we use to evaluate a number of different artificial agents.
Source: arXiv (Cornell University)
Authors: Legg, Shane, Veness, Joel
Institutions: Google DeepMind (United Kingdom), University of Alberta
Language: English
Subfield: Computational Theory and Mathematics
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2951801791