Linear genetic programming
- "Linear genetic programming" is unrelated to "linear programming".
Linear genetic programming (LGP) is a particular subset of genetic programming wherein computer programs in a population are represented as a sequence of instructions from imperative programming language or machine language. The graph-based data flow that results from a multiple usage of register contents and the existence of structurally noneffective code (introns) are two main differences of this genetic representation from the more common tree-based genetic programming (TGP) variant.
In genetic programming (GP) a linear tree is a program composed of a variable number of unary functions and a single terminal. Note linear tree GP differs from bit string genetic algorithms since a population may contain programs of different lengths and there may be more than two types of functions or more than two types of terminals.
Examples of LGP programs
Because LGP programs are basically represented by a linear sequence of instructions, they are simpler to read and to operate on than their tree-based counterparts. For example, a simple program written in the LGP language Slash/A looks like a series of instructions separated by a slash:
input/ # gets an input from user and saves it to register F 0/ # sets register I = 0 save/ # saves content of F into data vector D[I] (i.e. D := F) input/ # gets another input, saves to F add/ # adds to F current data pointed to by I (i.e. F := F + D) output/. # outputs result from F
- Brameier, M.: "On linear genetic programming", Dortmund, 2003
- W. Banzhaf, P. Nordin, R. Keller, F. Francone, "Genetic Programming – An Introduction. On the Automatic Evolution of Computer Programs and its Application", Morgan Kaufmann, Heidelberg/San Francisco, 1998
- Poli, R.; Langdon, W. B.; McPhee, N. F. (2008). A Field Guide to Genetic Programming. Lulu.com, freely available from the internet. ISBN 978-1-4092-0073-4.
- Foundations of Genetic Programming.