Ok that makes sense. These approaches are trying to add considerations such as mine into the model. Not sure I see how that can solve the issue of "the truth missing from the hypothesis space". Or how accurate modelling of the agents can be achieved at our current level of understanding. Examples of real world applications instead of abstract formulations would be really helpful but I will study the article on Solomonoff induction.
Not sure I see how that can solve the issue of "the truth missing from the hypothesis space".
Solomonoff Induction contains every possible (computable) hypothesis; so long as you're in a computable universe (and have logical omniscience), the truth is in your hypothesis space.
But this is sort of the trivial solution, because while it's guaranteed to have the right answer it had to bring in a truly staggering number of wrong answers to get it. It looks like what people do is notice when their models are being surprisingly bad, and then explicitl...
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