This article, published by OneNewsNow, quotes Casey Luskin of Discovery Institute: In November, the center released 44 pages of documents and claimed that all the records requested by the Discovery Institute were included. However, Casey Luskin, the program officer with the institute, claims that is not true. The rest of the article can be found here.
Seattle — World Magazine has named Stephen C. Meyer “Daniel of the Year,” their version of man of the year, for his groundbreaking work in explaining the evidence for intelligent design in his authoritative new book, Signature in the Cell: DNA and the Evidence for Intelligent Design (HarperOne). Meyer’s book has already made year-end lists with Amazon.com naming it one of Read More ›
This article, published by CBN News, quotes Discovery Institute Senior Fellow George Gilder: In his new book, The Israel Test author George Gilder said Israel is hated because it is successful, free, and good. Jews throughout history have contributed to humanity disproportionately. For example, Jews make up a miniscule proportion of the world’s population but have produced more than 20 Read More ›
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. We propose three measures to characterize the information required for successful search: 1) endogenous information, which measures the difficulty of finding a target using random search; 2) exogenous information, which measures the difficulty that remains in finding a target once a search takes advantage of problem-specific information; and 3) active information, which, as the difference between endogenous and exogenous information, measures the contribution of problem-specific information for successfully finding a target. This paper develops a methodology based on these information measures to gauge the effectiveness with which problem-specific information facilitates successful search. It then applies this methodology to various search tools widely used in evolutionary search.