Roughly speaking, a general search process is something which takes in a specification of some problem or objective (from a broad class of possible problems/objectives), and returns a plan which solves the problem or scores well on the objective.
This description of “search” seems far too broad. E.g., it seems to include things like lookup tables, and AFAICT, literally every way to solve problems or satisfy objectives?
Seems like “search” should mean something more specific than “problem solving”.
It excludes methods specific to a small number of problems. Search is about general problem solving.
Anyway, IIUC this is how the term “search” has historically been used in AI, it is also the notion of “search” which is relevant to the arguments for mesaoptimization in Risks From Learned Optimization, it is also the notion of search which is relevant to general intelligence being A Thing, it is the notion of search which is relevant to the possibility of an ML system suddenly grokking “general search” and thereby undergoing a rapid increase in capabilities, etc.
This description of “search” seems far too broad. E.g., it seems to include things like lookup tables, and AFAICT, literally every way to solve problems or satisfy objectives?
Seems like “search” should mean something more specific than “problem solving”.
It excludes methods specific to a small number of problems. Search is about general problem solving.
Anyway, IIUC this is how the term “search” has historically been used in AI, it is also the notion of “search” which is relevant to the arguments for mesaoptimization in Risks From Learned Optimization, it is also the notion of search which is relevant to general intelligence being A Thing, it is the notion of search which is relevant to the possibility of an ML system suddenly grokking “general search” and thereby undergoing a rapid increase in capabilities, etc.