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Universal Artificial Intelligence

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Last year I did a series of interviews with Marcus Hutter while he was down in Melbourne for the Singularity Summit Australia 2012.

Marcus will also be speaking at the [su_highlight]Science, Technology & the Future conference in Melbourne on Nov 30 – Dec 1 2013 in Melbourne, Australia.[/su_highlight]

Hutter uses Solomonoff’s inductive inference as a mathematical formalization of Occam’s razor. Hutter adds to this formalization the expected value of an action: shorter (Kolmogorov complexity) computable theories have more weight when calculating the expected value of an action across all computable theories which perfectly describe previous observations.

At any time, given the limited observation sequence so far, what is the Bayes-optimal way of selecting the next action? Hutter proved that the answer is to use Solomonoff’s universal prior to predict the probability of each possible future, and execute the first action of the best policy (a policy is any program that will output all the next actions and input all the next perceptions up to the horizon). A policy is the best if, on a weighted average of all the possible futures, it will maximize the predicted reward up to the horizon. He called this universal algorithm AIXI.

At Singularity Summit Australia 2012 – “Can Intelligence Explode?”
[su_youtube url=”http://www.youtube.com/watch?v=focaMjQbmkI”]

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