I’m having some trouble parsing what you have wrote.
Presumably I can determine whether any fixed prescription will cause me to attain my goal—I can simulate the universe and check the outcome at the end. Thus checking whether a particular sequence of actions (or a particular design, strategy, etc.) has the desired property is in P.
I don’t follow this line of reasoning at all. Whether a problem is in P is a statement about the length of time it takes in general to solve instances. Also, a problem for this purpose is a collection of questions of the form “for given input N, does N have property A?”
None of this is to say that P = NP sheds light on how easy these questions actually are, but P = NP is the normal theoretical interpretation, and in fact the only theoretical interpretation that makes sense if you are going to stick with the position that P is precisely the class of problems that an AI can solve.
I’m not sure what you mean by this. First of all, the general consensus is that P !=NP. Second of all, in no interpretation is P is somehow precisely the set of problems that an AI can solve. It seems you are failing to distinguish between instances of problems and the general problems. Thus for example, the traveling salesman problem is NP complete. Even if P != NP, I can still solve individual traveling salesman problems (you can probably solve any instance with fewer than five nodes more or less by hand without too much effort.). Similarly, even if factoring turns out to be not in P, it doesn’t mean anyone is going to have trouble factoring 15.
I’m having some trouble parsing what you have wrote.
I don’t follow this line of reasoning at all. Whether a problem is in P is a statement about the length of time it takes in general to solve instances. Also, a problem for this purpose is a collection of questions of the form “for given input N, does N have property A?”
I’m not sure what you mean by this. First of all, the general consensus is that P !=NP. Second of all, in no interpretation is P is somehow precisely the set of problems that an AI can solve. It seems you are failing to distinguish between instances of problems and the general problems. Thus for example, the traveling salesman problem is NP complete. Even if P != NP, I can still solve individual traveling salesman problems (you can probably solve any instance with fewer than five nodes more or less by hand without too much effort.). Similarly, even if factoring turns out to be not in P, it doesn’t mean anyone is going to have trouble factoring 15.