To save time, boring games such as random environments or one where the agent can 'die'* are excluded
* make a mistake which turns any future rewards into fixed rewards with no connection to future actions
This seems like a glaring bias in algorithm design... like it is somehow building anthropic craziness into the definition of intelligence on purpose? If I was trying to design something that maximized its score it would never bother to consider situations of possible death because they "don't count" in the context it is practicing within, where it is presumably deploying priors/habits/heuristics for use in other contexts. Generalizing this insight to other design or educational processes is kind of worry inducing...
'die' is my own term, since it seemed to be the game term analogous to 'when an agent makes a move that renders it causally unconnected to all future rewards' (again, my own description).
The problem with including games in which one can 'die' is that they take much longer to learn. Suppose the agent the first time it plays the game happens to 'die', and now it only experiences a steady stream of 1,1,1,1,1... (low rewards). Nothing it does changes its future rewards, so exploration (trying different moves) is penalized. Dying on the first move might look li...
"Measuring universal intelligence: Towards an anytime intelligence test"; abstract:
http://www.csse.monash.edu.au/~dld/Publications/HernandezOrallo+DoweArtificialIntelligenceJArticle.pdf
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.
* apparently no good overviews of the whole topic AIXI but you could start at http://www.hutter1.net/ai/aixigentle.htm or http://www.hutter1.net/ai/uaibook.htm
** 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