Extending Universal Intelligence Models with Formal Notion of Representation (Potapov and Rodionov)

Added by Deon Garrett about 6 years ago

Solomonoff induction is known to be universal, but incomputable. Its approximations, namely, the Minimum Description (or Message) Length (MDL) principles, are adopted in practice in the efficient, but non-universal form. Recent attempts to bridge this gap leaded to development of the Representational MDL principle that originates from formal decomposition of the task of induction. In this paper, possible extension of the RMDL principle in the context of universal intelligence agents is considered, for which introduction of representations is shown to be an unavoidable meta-heuristic and a step toward efficient general intelligence. Hierarchical representations and model optimization with the use of information-theoretic interpretation of the adaptive resonance are also discussed.

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Replies (5)

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RE: Extending Universal Intelligence Models with Formal Notion of Representation (Potapov and Rodionov) - Added by Khabib Abdul 11 days ago

The plan of universal induction and prediction on the basis of algorithmic analysis theory was discovered a long time ago. In summary, it eliminates the fundamental problem of prior probabilities, wrong solutions of which result in such negative practical impacts as overlearning, overfitting, and this goes on. It would be rather natural to try to develop some models of universal intelligence on this basis. This topic cannot be easy for the thesis students and for this we are providing Thesis writing for MBA students.

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