Shane Legg
Intelligence is a key concept in the quest for artificial intelligence, and more generally the singularity. Remarkably, relatively little work has gone into developing general, encompassing and theoretically founded definitions of intelligence for machines. This leaves us without a clear foundation for either theoretical research or developing empirical measures of progress. In this talk I outline the major perspectives on the nature of intelligence and some of the informal definitions that have been put forward. I then sketch the main ideas behind the universal intelligence measure. This is a formal definition of intelligence based on Hutter's AIXI model of theoretically optimal machine intelligence. Based on this a number of researchers, including myself, are developing practical tests of machine intelligence. I describe some of the challenges faced when doing this and share some recent results from testing various artificial agents. Might we soon be able to measure our progress towards machine intelligence?
