The definition of 'probabilistic consistency' that I was using
comes from
ET Jaynes' book _Probability Theory - The Logic of Science_, page
114.
These are Jaynes' three 'consistency desiderata' for a
probabilistic robot:
1. If a conclusion can be reasoned out in more than one way, then
every
possible way must lead to the same result.
2. The robot takes into account all information relevant to the
question.
3. The robot always represents equivalent states of information with
equivalent plausibility assignments.
I don't think any intelligent system (human or machine) can achieve
any of the three desiderata, except in trivial cases.
I agree with Pei. This is an "ideal probabilistic robot" which is
irrelevant to AGI.
I introduced such a mind as a theoretical tool in a prior email, but
you can't
build it except in toy domains.
ben
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