- author = "Simon Harding and Julian F. Miller and Wolfgang Banzhaf",
- title = "{SMCGP2}: self modifying cartesian genetic programming in two dimensions",
- booktitle = "GECCO '11: Proceedings of the 13th annual conference on Genetic and evolutionary computation",
- year = "2011",
- editor = "Natalio Krasnogor and Pier Luca Lanzi and Andries Engelbrecht and David Pelta and Carlos Gershenson and Giovanni Squillero and Alex Freitas and Marylyn Ritchie and Mike Preuss and Christian Gagne and Yew Soon Ong and Guenther Raidl and Marcus Gallager and Jose Lozano and Carlos Coello-Coello and Dario Landa Silva and Nikolaus Hansen and Silja Meyer-Nieberg and Jim Smith and Gus Eiben and Ester Bernado-Mansilla and Will Browne and Lee Spector and Tina Yu and Jeff Clune and Greg Hornby and Man-Leung Wong and Pierre Collet and Steve Gustafson and Jean-Paul Watson and Moshe Sipper and Simon Poulding and Gabriela Ochoa and Marc Schoenauer and Carsten Witt and Anne Auger",
- isbn13 = "978-1-4503-0557-0",
- pages = "1491--1498",
- keywords = "genetic algorithms, genetic programming, cartesian genetic programming, developmental systems",
- month = "12-16 " # jul,
- organisation = "SIGEVO",
- address = "Dublin, Ireland",
-
URL = "
http://www.cs.mun.ca/%7Ebanzhaf/papers/SMCGP2-2011.pdf",
-
DOI = "
doi:10.1145/2001576.2001777",
- publisher = "ACM",
- publisher_address = "New York, NY, USA",
- size = "8 pages",
- abstract = "Self Modifying Cartesian Genetic Programming 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 certain Boolean circuits and mathematical problems. In the present work, a new version, of SMCGP is proposed and demonstrated. Compared to the original SMCGP both the representation and the function set have been simplified. However, the new representation is also two-dimensional and it allows evolution and development to have more ways to solve a given problem. Under most situations we show that the new method makes the evolution of solutions to even parity and binary addition faster than with previous version of SMCGP.",
-
notes = "hill climbing. General solution to parity.
Also known as \cite{2001777} GECCO-2011 A joint meeting of the twentieth international conference on genetic algorithms (ICGA-2011) and the sixteenth annual genetic programming conference (GP-2011)",
