"Measuring universal intelligence: Towards an anytime intelligence test"; abstract:
In this paper, we develop the idea of a universal anytime intelligence test. The meaning of the terms “universal” and “anytime” is manifold here: the test should be able to measure the intelligence of any biological or artificial system that exists at this time or in the future. It should also be able to evaluate both inept and brilliant systems (any intelligence level) as well as very slow to very fast systems (any time scale). Also, the test may be interrupted at any time, producing an approximation to the intelligence score, in such a way that the more time is left for the test, the better the assessment will be. In order to do this, our test proposal is based on previous works on the measurement of machine intelligence based on Kolmogorov complexity and universal distributions, which were developed in the late 1990s (C-tests and compression-enhanced Turing tests). It is also based on the more recent idea of measuring intelligence through dynamic/interactive tests held against a universal distribution of environments. We discuss some of these tests and highlight their limitations since we want to construct a test that is both general and practical. Consequently, we introduce many new ideas that develop early “compression tests” and the more recent definition of “universal intelligence” in order to design new “universal intelligence tests”, where a feasible implementation has been a design requirement. One of these tests is the “anytime intelligence test”, which adapts to the examinee's level of intelligence in order to obtain an intelligence score within a limited time.
Example popular media coverage: http://www.sciencedaily.com/releases/2011/01/110127131122.htm
The group's homepage: http://users.dsic.upv.es/proy/anynt/
(There's an applet but it seems to be about constructing a simple agent and stepping through various environments, and no working IQ test.)
The basic idea, if you already know your AIXI*, is to start with simple programs** and then test the subject on increasingly harder ones. To save time, boring games such as random environments or one where the agent can 'die'*** are excluded and a few rules added to prevent gaming the test (by, say, deliberately failing on harder tests so as to be given only easy tests which one scores perfectly on) or take into account how slow or fast the subject makes predictions.
** simple as defined by Kolmogorov complexity; since KC is uncomputable, one of the computable variants - which put bounds on resource usage - is used instead
*** make a mistake which turns any future rewards into fixed rewards with no connection to future actions