Title :
Generalisation and domain specific functions in genetic programming
Author_Institution :
Dept. of Comput., Surrey Univ., Guildford, UK
Abstract :
This research presents an evaluation of user defined domain specific functions of genetic programming using relational learning problems, generalisation for this class of learning problems and learning bias. After providing a brief theoretical background, two sets of experiments are detailed: experiments and results concerning the Monk-2 problem and experiments attempting to evolve generalising solutions to parity problems with incomplete data sets. The results suggest that using non-problem specific functions may result in greater generalisation for relational problems
Keywords :
generalisation (artificial intelligence); genetic algorithms; learning (artificial intelligence); learning systems; Monk-2 problem; domain specific functions; experiments; generalisation; genetic programming; incomplete data sets; learning bias; parity problems; relational learning problems; Data mining; Encoding; Genetic programming; Learning systems; Training data;
Conference_Titel :
Evolutionary Computation, 2000. Proceedings of the 2000 Congress on
Conference_Location :
La Jolla, CA
Print_ISBN :
0-7803-6375-2
DOI :
10.1109/CEC.2000.870815