2011/09/27 by Shane Legg, Joel Veness, Legg, Shane +1 · 1 citation
Computer Science · #Algorithms and Data Compression #Artificial Intelligence (cs.AI) #Computability, Logic, AI Algorithms #Evolutionary Algorithms and Applications #FOS: Computer and information sciences
paper · pdf · doi:10.48550/arxiv.1109.5951
openalex publication_date 2011/09/27 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.