Abstract:
The field of Genetic Programming in
Artificial Intelligence strives to get computers to solve a
problem without explicitly coding a solution by a
programmer. Genetic Programming is a relatively new
technology, which comes under automatic
programming. After the initial work by John R. Koza in
genetic programming, much research work have been
done to discover data models in various datasets. These
work have been rather domain specific and little
attention has been given to develop generic framework
for modeling and experimenting with genetic
programming solutions for real world problems. This
paper discusses a project to develop a visual
environment, named as GPVLab, to design and
experiment with genetic programming solutions for real
world problems. GPVLab has successfully discovered
data models for various data sets and according to the
main evaluation it is evident that GPVLab can generate
solutions which provide better results in 56% of the
time. It is concluded that GPVLab can be used to model
genetic programming application very conveniently.
GPVLab can be used not only for discovering data
models but also doing various experiments in genetic
programming.
