By Nada Lavrac
Offering the reader with an in-depth figuring out of empirical inductive common sense programming ways - that could deal with imperfect facts and will be used to build wisdom bases for fixing sensible difficulties - this e-book additionally describes numerous sensible functions intimately and offers an outline of different present functions of inductive good judgment programming. The ebook is on the cutting edge of present learn: inductive common sense programming is an rising box on the intersection of computer studying and good judgment programming. It proposes new equipment for studying relational descriptions (dealing additionally with imperfect information) that may be seen as substitute equipment for good judgment software synthesis. The booklet additionally offers a veiw on inductive good judgment programming as a seek of the dependent house of common sense software clauses, which addresses the difficulty of seek complexity and seek heuristics intimately. empirical inductive common sense programming platforms (LINUS and mFOIL) are defined, in addition to a number of functions of those platforms.
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Extra resources for Inductive logic programming: techniques and applications
Example text
Using this method, the column-wise square of the distances from the mean column value can be computed. Summing these across the string length L and population P will compute the moment of inertia diversity measure for non-binary alphabet strings. Let us do this with one final example, comparing a population of six (P = 6) short (L = 4) DNA fragments (A = {A,C,T,G}), having values Ygene,individual equal to: Yn = A,Y2l = T,Y3l = T,Y4l = C Y12 = C, Y22 = T, Y32 = A, Y42 = T Y13 = T, Y23 = G, Y33 = T, Y43 = C 40 4 Diversity Measurement = G,Y24 = G,Y34 = G,Y44 = G Y15 = A,Y25 = C,Y35 = G,Y45 = G Y16 = T,Y26 = C,Y36 = A,Y46 = G.
This is because, when using genotypic measures, all bit-wise diversity is treated the same, but differences at various bit positions can represent significantly different levels of phenotypic diversity. Despite this logical preference, genotypic measures are much more common in the EA literature. , [31]). 2) f(Xk,Xk'), k'=k+l is the sum of the results of the application of f(Xk, Xk') to all pair-wise combinations of the members Xk and Xk' of a given population of size M. 3) The most commonly used measures of population diversity include pairwise Hamming distance in genotypic space, and column-based pair-wise distance and column variance in phenotypic space.
This means that x 2 = x and x times x' is equal to x or x', or both. As a simplified example of how this computational method is used, consider a population of six strings (P = 6), each three bits long and having values Ygene,individual equal to: Yll = Y12 = 0, Y22 = 0, Y32 = 0 Y13 = 1,Y23 = Y14 = l'Y24 = 0,Y34 = 0 Y15 = 0,Y25 = Y16 = 1, Y26 = 0, Y36 = 1,Y21 = 1,Y31 1,Y33 1,Y35 =1 =0 =0 1. 21 ) r ~r ~r ~r is computed as: 6 [ (1 - ~ + (0 - + (1- + (1- + (0 - ~) 2 + (1- ~ r] +6 [ (1 _ ~) 2+ (0 _ ~) 2+ (1 _ ~) 2+ (0 _ ~) 2+ (1 _ ~) 2+ (0 _ ~) 2] +6 [ (1 _ ~) 2+ (0 _ ~) 2+ (0 _ ~) 2+ (0 _ ~) 2+ (0 _ ~) 2+ (1 _ ~) 2] 12 6 12) = (8 + 9 + 8) = 25 = 6(9 + 4+ 9 which is the same value as the pair-wise Hamming distance for this population.