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PierreD

Hi,

A way to get priors for a problem can be to re-use some knowledge from other similar issues.

This kind of "transfer learning" is applied in this paper:

http://www.icml2006.org/icml_documents/camera-ready/090_Constructing_Informa.pdf

The good point of bayes rule is that some posteriors can become prior for another problem. Placing this feature on a time line (ie the life of the learning agent), we can imagine the agent starting with poor prior and refining, generalizing it after experience.
It reminds me the field of "developmental robotics" were agents have a strategy to choose new problems on wich they can learn a lot.

Cheers,
Pierre

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