Phase transition and New Fitness Function based Genetic Inductive Logic Programming algorithm

Author(s):  
Yanjuan Li ◽  
Maozu Guo
2019 ◽  
Vol 12 (1) ◽  
pp. 89-104
Author(s):  
Yanjuan Li ◽  
Mengting Niu ◽  
Jifeng Guo

Inductive logic programming (ILP) is a hot research field in machine learning. Although ILP has obtained great success in many domains, in most ILP system, deterministic search are used to search the hypotheses space, and they are easy to trap in local optima. To overcome the shortcomings, an ILP system based on artificial bee colony (ABCILP) is proposed in this article. ABCILP adopts an ABC stochastic search to examine the hypotheses space, the shortcoming of deterministic search is conquered by stochastic search. ABCILP regard each first-order rule as a food source and propose some discrete operations to generate the neighborhood food sources. A new fitness is proposed and an adaptive strategy is adopted to determine the parameter of the new fitness. Experimental results show that: 1) the proposed new fitness function can more precisely measure the quality of hypothesis and can avoid generating an over-specific rule; 2) the performance of ABCILP is better than other systems compared with it.


1996 ◽  
Vol 9 (4) ◽  
pp. 157-206 ◽  
Author(s):  
Nada Lavrač ◽  
Irene Weber ◽  
Darko Zupanič ◽  
Dimitar Kazakov ◽  
Olga Štěpánková ◽  
...  

Author(s):  
Rinaldo Lima ◽  
Bernard Espinasse ◽  
Hilário Oliveira ◽  
Rafael Ferreira ◽  
Luciano Cabral ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document