TY - GEN
T1 - MT-CGP: Mixed type cartesian genetic programming
AU - Harding, Simon
AU - Graziano, Vincent
AU - Leitner, Jürgen
AU - Schmidhuber, Jürgen
N1 - Generated from Scopus record by KAUST IRTS on 2022-09-14
PY - 2012/8/13
Y1 - 2012/8/13
N2 - The majority of genetic programming implementations build expressions that only use a single data type. This is in contrast to human engineered programs that typically make use of multiple data types, as this provides the ability to express solutions in a more natural fashion. In this paper, we present a version of Cartesian Genetic Programming that handles multiple data types. We demonstrate that this allows evolution to quickly find competitive, compact, and human readable solutions on multiple classification tasks. © 2012 ACM.
AB - The majority of genetic programming implementations build expressions that only use a single data type. This is in contrast to human engineered programs that typically make use of multiple data types, as this provides the ability to express solutions in a more natural fashion. In this paper, we present a version of Cartesian Genetic Programming that handles multiple data types. We demonstrate that this allows evolution to quickly find competitive, compact, and human readable solutions on multiple classification tasks. © 2012 ACM.
UR - http://dl.acm.org/citation.cfm?doid=2330163.2330268
UR - http://www.scopus.com/inward/record.url?scp=84864645762&partnerID=8YFLogxK
U2 - 10.1145/2330163.2330268
DO - 10.1145/2330163.2330268
M3 - Conference contribution
SN - 9781450311779
SP - 751
EP - 758
BT - GECCO'12 - Proceedings of the 14th International Conference on Genetic and Evolutionary Computation
ER -