I agree! I think that it this is hard for humans working with current syntactic machinary to specify things like:
* what their decision thoery will return for every decision problem
* what split(DT_1,DT_2) looks like
Right now I think doing this requires putting all decision theories on a useful shared ontology. The way that UTMs put all computable algorithms on a useful shared ontology which allowed people to make proofs about algorithms in general. This looks hard and possibly requires creating new kinds of math.
I am making the assumption here that the decision theories are rescued to the point of being executable philosophy. DTs need to be specified this much to be run by an AI. I believe that the fuzzy concepts inside people’s heads about how can in principle be made to work mathematically and then run on a computer. In a similar way that the fuzzy concept of “addition” was ported to symbolic representations and then circuits in a pocket calculator.
I agree! I think that it this is hard for humans working with current syntactic machinary to specify things like:
* what their decision thoery will return for every decision problem
* what split(DT_1,DT_2) looks like
Right now I think doing this requires putting all decision theories on a useful shared ontology. The way that UTMs put all computable algorithms on a useful shared ontology which allowed people to make proofs about algorithms in general. This looks hard and possibly requires creating new kinds of math.
I am making the assumption here that the decision theories are rescued to the point of being executable philosophy. DTs need to be specified this much to be run by an AI. I believe that the fuzzy concepts inside people’s heads about how can in principle be made to work mathematically and then run on a computer. In a similar way that the fuzzy concept of “addition” was ported to symbolic representations and then circuits in a pocket calculator.