Strongly Typed Genetic Programming Export

@article{citeulike:5784895, abstract = {Genetic programming is a powerful method for automatically generating computer programs via the process of natural selection (Koza, 1992). However, in its standard form, there is no way to restrict the programs it generates to those where the functions operate on appropriate data types. In the case when the programs manipulate multiple data types and contain functions designed to operate on particular data types, this can lead to unnecessarily large search times and/or unnecessarily poor generalization performance. Strongly typed genetic programming (STGP) is an enhanced version of genetic programming which enforces data type constraints and whose use of generic functions and generic data types makes it more powerful than other approaches to type constraint enforcement. After describing its operation, we illustrate its use on problems in two domains, matrix/vector manipulation and list manipulation, which require its generality. The examples are: (1) the multi-dimensional least-squares regression problem, (2) the multi-dimensional Kalman filter, (3) the list manipulation function NTH, and (4) the list manipulation function MAPCAR.}, author = {Montana, David J.}, citeulike-article-id = {5784895}, citeulike-linkout-0 = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.38.4986}, citeulike-linkout-1 = {http://web.archive.org/web/20070814014654/http://vishnu.bbn.com/papers/stgp.pdf}, comment = {See also July 1993 BBN Technical Report \#7866 of the same name -- http://www.citeulike.org/user/numata/article/219660}, journal = {Evolutionary Computation}, keywords = {algorithm, emergence, evolution, gp, optimization, self\_organizing}, number = {2}, pages = {199--230}, posted-at = {2009-09-15 02:00:13}, priority = {2}, title = {Strongly Typed Genetic Programming}, url = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.38.4986}, volume = {3}, year = {1995} }

TY - JOUR ID - citeulike:5784895 L3 - citeulike-article-id:5784895 N2 - Genetic programming is a powerful method for automatically generating computer programs via the process of natural selection (Koza, 1992). However, in its standard form, there is no way to restrict the programs it generates to those where the functions operate on appropriate data types. In the case when the programs manipulate multiple data types and contain functions designed to operate on particular data types, this can lead to unnecessarily large search times and/or unnecessarily poor generalization performance. Strongly typed genetic programming (STGP) is an enhanced version of genetic programming which enforces data type constraints and whose use of generic functions and generic data types makes it more powerful than other approaches to type constraint enforcement. After describing its operation, we illustrate its use on problems in two domains, matrix/vector manipulation and list manipulation, which require its generality. The examples are: (1) the multi-dimensional least-squares regression problem, (2) the multi-dimensional Kalman filter, (3) the list manipulation function NTH, and (4) the list manipulation function MAPCAR. IS - 2 JF - Evolutionary Computation EP - 230 TI - Strongly Typed Genetic Programming VL - 3 SP - 199 KW - algorithm KW - emergence KW - evolution KW - gp KW - optimization KW - self_organizing N1 - See also July 1993 BBN Technical Report #7866 of the same name -- http://www.citeulike.org/user/numata/article/219660 AU - Montana, David PY - 1995/// UR - http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.38.4986 ER -