cousin_it comments on Bayesian probability as an approximate theory of uncertainty? - Less Wrong

16 Post author: cousin_it 26 September 2013 09:16AM

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Comment author: cousin_it 30 September 2013 07:57:00PM *  2 points [-]

The UDT solution says: "instead of drawing a graph containing <you>, draw one that contains <your abstract decision algorithm> and you will see that the independence between beliefs and decisions is restored!"

Can you try to come up with a situation where that independence is not restored? If we follow the analogy with correlations, it's always possible to find a linear map that decorrelates variables...

Comment author: alexflint 01 October 2013 02:35:19AM 0 points [-]

Ha, indeed. I should have made the analogy with finding a linear change of variables such that the result is decomposable into a product of independent distributions -- ie if (x,y) is distributed on a narrow band about the unit circle in R^2 then there is no linear change of variables that renders this distribution independent, yet a (nonlinear) change to polar coordinates does give independence.

Perhaps the way to construct a counterexample to UDT is to try to create causal links between <your decision algorithm> and <the world> of the same nature as the links between <you> and the <world> in e.g. Newcomb's problem. I haven't thought this through any further.