SMCGP2: finding algorithms that approximate numerical constants using quaternions and complex numbers

Authors:
Simon Harding;Julian F. Miller;Wolfgang Banzhaf
Affiliations:
Memorial University, St John's, Canada;University of York, York, United Kingdom;Memorial University, St John's, Canada
Venue:
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
Year:
2011

Citing 3
Cited 1

Self-modifying cartesian genetic programming

Proceedings of the 9th annual conference on Genetic and evolutionary computation
Self modifying cartesian genetic programming: finding algorithms that calculate pi and e to arbitrary precision

Proceedings of the 12th annual conference on Genetic and evolutionary computation
SMCGP2: self modifying cartesian genetic programming in two dimensions

Proceedings of the 13th annual conference on Genetic and evolutionary computation

SMCGP2: self modifying cartesian genetic programming in two dimensions

Proceedings of the 13th annual conference on Genetic and evolutionary computation

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Abstract

Self Modifying Cartesian Genetic Programming 2 (SMCGP2) is a general purpose, graph-based, developmental form of Cartesian Genetic Programming. Using a combination of computational functions and special functions that can modify the phenotype at runtime, it has been employed to find general solutions to a number of computational problems. Here, we apply the new SMCGP technique to find mathematical relationships between well known mathematical constants (i.e. pi, e, phi, omega etc) using a variety of functions sets. Some of formulae obtained are distinctly unusual and may be unknown in mathematics.