For some time now, objector DiEb has been raising the question, what do we mean by speaking of “search” in the context of evolutionary search. At 311 in the parody thread, she [IIRC] remarks:
>>Search is a central term in the work of Dr. Dr. William Dembski jr, Dr. Winston Ewert, and Dr. Robert Marks II (DEM): it appears in the title of a couple of papers written by at least two of the authors, and it is mentioned hundreds of times in their textbook “Introduction to Evolutionary Informatics“. Strangely – and in difference from the other central term information, it is not defined in this textbook, and neither is search problem or search algorithm. Luckily, dozens of examples of searches are given. I took a closer look to find out what DEM see as the search problem in the “Introduction to Evolutionary Informatics” and how their model differs from those used by other mathematicians and scientists.
I have responded yet again to the basic conceptual point (regardless of debate points re Marks, Dembski et al) to draw out why search challenge is a pivotal concern in the discussion of the design inference, based on the issue of large configuration spaces and islands of function, similar to Abel’s discussion of a decade or so ago in the peer-reviewed literature on the universal PLAUSIBILITY metric, principle and bound. I therefore consider it worth the while to headline as follows:
KF, 338: >>Several times, you have raised the issue of search. I have pointed out that at base, it is tantamount to sampling from a configuration space.
[As, algebraic representation is commonly desired (and is often deemed superior to illustration or verbal description), a traditional representation of such a space is to symbolise it as Omega, here we can use w. Search then is obviously — and the obviousness is a material point here — tantamount to taking a subset of cases k in w by whatever relevant means, blind or intelligent. The search challenge then is to find some relevant zone z in w such that a performance based on configuration rises above a floor deemed non-functional: find/happen upon some z_i in w such that p(z) GT/eq f_min. Zones z are islands of function in the configuration space, w.]
[Let’s add a cluster of UD infographics over the years:]
In the sense, blind search, by chance and/or mechanical necessity without intelligent direction or control or guidance or influence generally. This is directly relevant to the challenge of “finding” — strictly, happening upon the shorelines of — deeply isolated islands of function in config spaces of 500 – 1,000 bits or more of complexity. In these cases,
a: the atomic resources of the sol system or observed cosmos [10^57 to 10^80 atoms, more or less]
b: treated as observers each sampling at fast chemical reaction rates [~10^14 samples or observations/sec]
c: for 10^17 s (order of time since the typical projection to the singularity) will be
d: utterly overwhelmed by the scope of search to plausibly sample enough of the space to credibly hit one or more shorelines of function.
This does not require any detailed probability assessment, but indicates that by many orders of magnitude the challenge overwhelms the search resources.
As a direct result, blind search is not a plausible means of discovering zones exhibiting functionally specific complex organisation and/or associated information [FSCO/I] in sufficiently complex configuration spaces.
Where, per search samples the space, it is a subset, so the set of possible searches is comparable to the power set. If the direct set is of magnitude n, the set of searches is comparable in magnitude to 2^n. Thus, search for a golden search is plausibly exponentially harder than direct search.
Of course, typical discussions of fitness landscapes are about incremental hill-climbing within islands of function. They thus beg the question of arriving at shorelines of function. Where also, deep isolation is a direct result of FSCO/I requiring multiple, well matched components properly arranged and coupled to produce relevant results.
And as a consequence of OOL requiring credibly 100k – 1,000 k bases and body plans 10 – 100 millions, we are well beyond the FSCO/I threshold in these cases.
So, it is not plausible that the FSCO/I seen in life forms at origin or at basic body plan level, originated by blind search.
Pausing, it is worth noting that the proposal that ability to reproduce leading to descent with incremental modification solves the problem typically overlooks that at OOL, there is need to account for the FSCO/I of the von Neumann kinematic self-replicator found in the living cell.
Likewise, that for body plan origins, many co-ordinated changes (often, involving reproduction) will have to be accounted for. Natural selection of reproducing entities does not evade the origin of FSCO/I challenge.
What, per Newton’s vera causa principle, has right to be regarded as an observed effective cause of FSCO/I? Intelligently directed configuration, aka design.
Indeed, we are well within our inductive logic, epistemic rights, to hold that FSCO/I is a well tested, highly reliable sign of design as materially relevant cause. On a trillion member observation base.>>
Consequently, we have a reasonable and robust baseline understanding of search and of search challenge that then drives reflection on the inductive logic, empirically justified design inference explanatory filter, here seen in the per aspect in succession form:
Thus, the design inference is an empirically grounded, robust framework for exploring origin of FSCO/I. And, it is testable by the simple means of identifying observed cases of origin of FSCO/I rich entities and evaluating whether blind search credibly and reliably causes FSCO/I. To date, on a trillion member observation base, no. END