Evolutionary Algorithms and ID

[Dan_Eastwood]

FYI: There is extended discussion of the Safes and Thieves example here:

Comments on Gpuccio: Functional Information Methodology

@gpuccio here is a reference point for the discussion. This definition is from Hazen and Szostak. I(Ex) = ?log2[F(Ex)], where F(Ex) is the fraction of all possible configurations of the system that possess a degree of function ? Ex. Functional information, which we illustrate with letter sequences, artificial life, and biopolymers, thus represents the probability that an arbitrary configuration of a system will achieve a specific function to a specified degree. In each case we observe evidence for several distinct solutions with different maximum degrees of function, features that lead to steps in plots of information versus degree of function.

And here:

Information is Additive but Evolutionary Wait Time is Not

Actually the opposite. he thinks it must happen all at once. He needs that, because it MUST happen at all at once for his wait time = 2^FI claim to be correct. Decomposable and parallel are distinct concepts. A decomposable, but non-parallel, problem would change this: To this: In fully decomposible system (100 safes) the wait time is about 100 * 2 . Here one thief is working, solving each safe one at a time. Exactly, so this last case is just not relevant. There is at least two other simplifications in this case study, which if we fixed, it would even further decrease wait time to be sublinear.