Interesting
However, to me, it appears that with games the purpose is to win. Games have a end point
A powerful learning AI would be able to store a larger number of end points for a particular game than a human gamer. Not a given but likely
Protein folding computer simulations are being used, although it seems not in a learning game situation
Nowadays, researchers predict the structure of a protein by inputting the amino acid sequence into a computer. The advanced technology and modeling software allow scientists and researchers to form a predicted structure. However, the structure is not accurate, as there is always a small degree of errors present. Nevertheless, this can speed up discovery of new medications since the digital structure can be manipulated.
https://en.m.wikibooks.org/wiki/Structural_Biochemistry/Proteins/Protein_Folding_Problem
I may be off base but these situations appear to being worked backwards
Scientists KNOW the result, just require to understand how the end point was reached ie reverse the folding and find what initiated each fold
The problem stated in the extract is
- the structure is not accurate and
- there is always a small degree of errors present
Can these be overcome by a learning AI? or just putting in more precise details?
Sorry don't know
Again interesting. It would be much more than interesting to plug in the parameters and target protein and find a learning AI finds more than one fold configuration produces same target protein