About Measuring the Cost of Success

William A. Dembski, and Robert J. Marks II authored the paper Measuring the Cost of Success. Quoting from the abstract:

Abstract—Conservation of information theorems indicate that any search algorithm performs, on average, as well as random search without replacement unless it takes advantage of problem-specific information about the search target or the search-space structure. Combinatorics shows that even a moderately sized search requires problem-specific information to be successful. Computers, despite their speed in performing queries, are completely inadequate for resolving even moderately sized search problems without accurate information to guide them.

The subject matter is relevant to origin of life and evolutionary scenarios since both must account for the development of information systems in biological organisms. Search algorithms should accurately model biological processes. If genetic changes are random with respect to the reproductive fitness of a self-replicator, then how would a moderately sized search for a target enhancing reproductive fitness succeed without front loading the search with the problem-specific information needed to locate the target?

Counterarguments to Behe's irreducible complexity concept have suggested specific intermediate evolutionary structures and functions en route to the evolution of the systems Behe cited. This paper of Dembski and Marks appears applicable to those types of scenarios. Behe's search target is specified and precursor biological systems nominated as plausible candidates by Behe's critics.