Morendil comments on Book Club Update and Chapter 1 - Less Wrong

15 Post author: Morendil 15 June 2010 12:30AM

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Comment author: cata 16 June 2010 10:14:13PM *  2 points [-]

I think I was unclear. Here's what I mean:

Suppose our robot takes these two propositions:

A = "It's going to rain tonight in Michigan." B = "England will win the World Cup."

And suppose it thinks that the plausibility of A is 40, and the plausibility of B is 25.

As far as our robot knows, these propositions are not related. That is, in Jaynes' notation (I'll use a bang for "not,") (A|B) = (A|!B) = 40, and (B|A) = (B|!A) = 25. Is that correct?

Now suppose that the plausibility of A jumps to 80, because it's looking very cloudy this afternoon. I suggest that the plausibility of B should remain unchanged. I'm not sure whether the current set of rules is sufficient to ensure that, although I suspect it is. I think it might be impossible to come up with a consistent system breaking this rule that still obeys the (3c) "consistency over equivalent problems" rule.

Comment author: Morendil 17 June 2010 06:16:36AM 2 points [-]

If you know from the outset that these propositions are unrelated, you already know something quite important about the logical structure of the world that these propositions describe.

Jaynes comes back to this point over and over again, and it's also a major theme of the early chapters in Pearl's Causality:

Probabilistic relationships, such as marginal and conditional independencies, maybe helpful in hypothesizing initial causal structures from uncontrolled observations. However, once knowledge is cast in causal structure, those probabilistic relationships tend to be forgotten; whatever judgements people express about conditional independencies in a given domain are derived from the causal structure acquired. This explains why people feel confident asserting certain conditional independencies (e.g., that the price of beans in China is independent of the traffic in Los Angeles) having no idea whatsoever about the numerical probabilities involved (e.g., whether the price of beans will exceed $10 per bushel).

-- Pearl, Causality p. 25