%0 Conference Paper %1 whigham:1995:ingp %A Whigham, P. A. %B First International Conference on Genetic Algorithms in Engineering Systems: Innovations and Applications, GALESIA %C Sheffield, UK %D 1995 %E Zalzala, A. M. S. %I IEE %K algorithms, context free genetic grammar programming, %P 461--466 %T Inductive Bias and Genetic Programming %U http://ieeexplore.ieee.org/iel3/3532/10616/00501939.pdf?tp=&arnumber=501939&isnumber=10616 %V 414 %X Many engineering problems may be described as a search for one near optimal description amongst many possibilities, given certain constraints. Search techniques such as genetic programming, seem appropriate to represent many problems. The paper describes a grammatically based learning technique based upon the genetic programming paradigm, that allows declarative biasing and modifies the bias as the evolution proceeds. The use of bias allows complex problems to be represented and searched efficiently %@ 0-85296-650-4

@inproceedings{whigham:1995:ingp, abstract = {Many engineering problems may be described as a search for one near optimal description amongst many possibilities, given certain constraints. Search techniques such as genetic programming, seem appropriate to represent many problems. The paper describes a grammatically based learning technique based upon the genetic programming paradigm, that allows declarative biasing and modifies the bias as the evolution proceeds. The use of bias allows complex problems to be represented and searched efficiently}, added-at = {2008-06-19T17:35:00.000+0200}, address = {Sheffield, UK}, author = {Whigham, P. A.}, biburl = {https://www.bibsonomy.org/bibtex/2a1bf11de2d604769a7a37ddd50c3a21f/brazovayeye}, booktitle = {First International Conference on Genetic Algorithms in Engineering Systems: Innovations and Applications, GALESIA}, editor = {Zalzala, A. M. S.}, interhash = {1ee2d6e4465631bca425fa05e38ee852}, intrahash = {a1bf11de2d604769a7a37ddd50c3a21f}, isbn = {0-85296-650-4}, keywords = {algorithms, context free genetic grammar programming,}, month = {12-14 September}, notes = {12--14 September 1995, Halifax Hall, University of Sheffield, UK see also http://www.iee.org.uk/LSboard/Conf/program/galprog.htm Using 6-multiplexor problem shows using a syntax (of the correct sort, specified using a context free grammar) to constrain the form of the program trees helps GP solve the problem. More restrictions, easier it is. Then presents a method based on the syntax of the fitest member of the population to modify the grammar whilst the GP runs. Shows improvement on 6-multiplexor. Still greater improvements obtained by introducing a fitness for rules within the grammar. This weakly biases the grammar, ie all legal program are still legal, but now some are more likley to be produced than they where before the fitness of the grammar rules where changed. 10\% of population each generation regenerated using his {"}replacement{"} operator.}, pages = {461--466}, publisher = {IEE}, publisher_address = {London, UK}, timestamp = {2008-06-19T17:54:07.000+0200}, title = {Inductive Bias and Genetic Programming}, url = {http://ieeexplore.ieee.org/iel3/3532/10616/00501939.pdf?tp=&arnumber=501939&isnumber=10616}, volume = 414, year = 1995 }