%0 Book Section %1 yu:2005:recurse %A Yu, Tina %B Genetic Programming Theory and Practice III %C Ann Arbor %D 2005 %E Yu, Tina %E Riolo, Rick L. %E Worzel, Bill %I Springer %K Fibonacci Haskell PolyGP, abstraction, algorithms, filter, foldr, functional functions, genetic higher-order lambda languages, patterns, programming programming, recursion recursion, scanr, sequence, strstr, systems, type %P 93--108 %T A Higher-Order Function Approach to Evolve Recursive Programs %V 9 %X We demonstrate a functional style recursion implementation to evolve recursive programs. This approach re-expresses a recursive program using a non-recursive application of a higher-order function. It divides a program recursion pattern into two parts: the recursion code and the application of the code. With the higher-order functions handling recursion code application, GP effort becomes focused on the generation of recursion code. We employed this method to evolve two recursive programs: strstr C library function and programs that produce the Fibonacci sequence. In both cases, the program space defined by higher-order functions are very easy for GP to find a solution. We have learned about higher-order function selection and fitness assignment through this study. The next step will be to test the approach on applications with open-ended solutions, such as evolutionary design. %& 7 %@ 0-387-28110-X

@incollection{yu:2005:recurse, abstract = {We demonstrate a functional style recursion implementation to evolve recursive programs. This approach re-expresses a recursive program using a non-recursive application of a higher-order function. It divides a program recursion pattern into two parts: the recursion code and the application of the code. With the higher-order functions handling recursion code application, GP effort becomes focused on the generation of recursion code. We employed this method to evolve two recursive programs: strstr C library function and programs that produce the Fibonacci sequence. In both cases, the program space defined by higher-order functions are very easy for GP to find a solution. We have learned about higher-order function selection and fitness assignment through this study. The next step will be to test the approach on applications with open-ended solutions, such as evolutionary design.}, added-at = {2008-06-19T17:35:00.000+0200}, address = {Ann Arbor}, author = {Yu, Tina}, biburl = {https://www.bibsonomy.org/bibtex/247dd5812dd9d1a02f0f940d6949cb7d5/brazovayeye}, booktitle = {Genetic Programming Theory and Practice {III}}, chapter = 7, editor = {Yu, Tina and Riolo, Rick L. and Worzel, Bill}, interhash = {ec30e4026d00e3c925d7e4bd91c2374c}, intrahash = {47dd5812dd9d1a02f0f940d6949cb7d5}, isbn = {0-387-28110-X}, keywords = {Fibonacci Haskell PolyGP, abstraction, algorithms, filter, foldr, functional functions, genetic higher-order lambda languages, patterns, programming programming, recursion recursion, scanr, sequence, strstr, systems, type}, month = {12-14 May}, notes = {part of \cite{yu:2005:GPTP} Published Jan 2006 after the workshop}, pages = {93--108}, publisher = {Springer}, series = {Genetic Programming}, size = {16 pages}, timestamp = {2008-06-19T17:55:04.000+0200}, title = {A Higher-Order Function Approach to Evolve Recursive Programs}, volume = 9, year = 2005 }