Cartesian genetic programming: Difference between revisions

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Cartesian genetic programming is a form of [[genetic programming]], which uses a graph representation to encode computer programs. It grew from a method of evolving digital circuits developed by Miller et al. in 1997<ref>Miller, J.F., Thomson, P., Fogarty, T.C.: Designing Electronic Circuits Using Evolutionary Algorithms: Arithmetic Circuits: A Case Study. In: D. Quagliarella, J. Periaux, C. Poloni, G. Winter (eds.) Genetic Algorithms and Evolution Strategies in Engineering and Computer Science: Recent Advancements and Industrial Applications, pp. 105–131. Wiley (1998)</ref>. However the term ‘Cartesian genetic programming’ first appeared in 1999<ref> Miller, J.F.: An Empirical Study of the Efficiency of Learning Boolean Functions using a Cartesian Genetic Programming Approach. In: Proc. Genetic and Evolutionary Computation Conference, pp. 1135–1142. Morgan Kaufmann (1999)</ref> and was proposed as a general form of genetic programming in 2000<ref> Miller, J.F., Thomson, P.: Cartesian Genetic Programming. In: Proc. European Conference on

Genetic Programming, LNCS, vol. 1802, pp. 121–132. Springer (2000)</ref>. It is called ‘Cartesian’ because it represents a program using a two-dimensional grid of nodes.

== References ==

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