You keep trying to guess proper caveats, I can giving you trivial counterexamples.
This one has: range over entire R, values in [-11,+10], average value 0, global maximum 10, average of local maxima −2.6524 ?
Any function which is more bumpy when it’s low, and more smooth when it’s high will be like that. This particular one chosen for prettiness of visualization.
Any function which is more bumpy when it’s low, and more smooth when it’s high will be like that.
That’s what I just said:
Only if the space is constructed to have more local maxima when f(x) is small,
You are hyper-focusing on this as if it made a difference to my proofs. Please note my previous comment: It does not matter; I never talked about the average IC over all possible agents. I only spoke of IC over various recombinations of existing agents, all of which I assumed to have IC that are local minima. The “random agent” is not an agent taken from the whole space; it’s an agent gotten by recombining values from the existing agents.
How about this function?
You keep trying to guess proper caveats, I can giving you trivial counterexamples.
This one has: range over entire R, values in [-11,+10], average value 0, global maximum 10, average of local maxima −2.6524 ?
Any function which is more bumpy when it’s low, and more smooth when it’s high will be like that. This particular one chosen for prettiness of visualization.
That’s what I just said:
You are hyper-focusing on this as if it made a difference to my proofs. Please note my previous comment: It does not matter; I never talked about the average IC over all possible agents. I only spoke of IC over various recombinations of existing agents, all of which I assumed to have IC that are local minima. The “random agent” is not an agent taken from the whole space; it’s an agent gotten by recombining values from the existing agents.