Developments in Cartesian Genetic Programming: self-modifying CGP

Self-modifying Cartesian Genetic Programming (SMCGP) is a general purpose, graph-based, developmental form of Genetic Programming founded on Cartesian Genetic Programming. In addition to the usual computational functions, it includes functions that can modify the program encoded in the genotype. Thi...

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Bibliographic Details
Published in:Genetic programming and evolvable machines 2010-09, Vol.11 (3-4), p.397-439
Main Authors: Harding, Simon, Miller, Julian F., Banzhaf, Wolfgang
Format: Article
Language:English
Subjects:
Approximation
Artificial Intelligence
Biomedical Engineering and Bioengineering
Cartesian
Compilers
Computation
Computer Science
Contributed Article
Electrical Engineering
Genetics
Interpreters
Iterative methods
Mathematical analysis
Mathematical models
Programming
Programming Languages
Programming Techniques
Software Engineering/Programming and Operating Systems
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Summary:Self-modifying Cartesian Genetic Programming (SMCGP) is a general purpose, graph-based, developmental form of Genetic Programming founded on Cartesian Genetic Programming. In addition to the usual computational functions, it includes functions that can modify the program encoded in the genotype. This means that programs can be iterated to produce an infinite sequence of programs (phenotypes) from a single evolved genotype. It also allows programs to acquire more inputs and produce more outputs during this iteration. We discuss how SMCGP can be used and the results obtained in several different problem domains, including digital circuits, generation of patterns and sequences, and mathematical problems. We find that SMCGP can efficiently solve all the problems studied. In addition, we prove mathematically that evolved programs can provide general solutions to a number of problems: n -input even-parity, n -input adder, and sequence approximation to π.
ISSN:1389-2576
1573-7632
DOI:10.1007/s10710-010-9114-1