A NEW LINEAR GENETIC PROGRAMMING APPROACH BASED ON STRAIGHT LINE PROGRAMS: SOME THEORETICAL AND EXPERIMENTAL ASPECTS-Reference-Cited by-同舟云学术

A NEW LINEAR GENETIC PROGRAMMING APPROACH BASED ON STRAIGHT LINE PROGRAMS: SOME THEORETICAL AND EXPERIMENTAL ASPECTS

Published:2009-10 Issue:05 Volume:18 Page:757-781
ISSN:0218-2130
Container-title:International Journal on Artificial Intelligence Tools
language:en
Short-container-title:Int. J. Artif. Intell. Tools

Author:

ALONSO CÉSAR L.¹,MONTAÑA JOSÉ LUIS²,PUENTE JORGE¹,BORGES CRUZ ENRIQUE²

Affiliation:

1. Centro de Inteligencia Artificial, Universidad de Oviedo, Campus de Viesques 33271 Gijón, Spain

2. Dpto. de Matemáticas Estadística y Computación, Universidad de Cantabria, Avda de los Castros Santander, Spain

Abstract

Tree encodings of programs are well known for their representative power and are used very often in Genetic Programming. In this paper we experiment with a new data structure, named straight line program (slp), to represent computer programs. The main features of this structure are described, new recombination operators for GP related to slp's are introduced and a study of the Vapnik-Chervonenkis dimension of families of slp's is done. Experiments have been performed on symbolic regression problems. Results are encouraging and suggest that the GP approach based on slp's consistently outperforms conventional GP based on tree structured representations.

Publisher

World Scientific Pub Co Pte Ltd

Subject

Artificial Intelligence,Artificial Intelligence

Link

https://www.worldscientific.com/doi/pdf/10.1142/S0218213009000391

Reference18 articles.

1. Genetic Programming

2. P. Nordin, Advances in Genetic Programming, ed. K. E. Kinnear (MIT Press, Cambridge MA, 1994) pp. 311–331.

3. Algebraic Complexity Theory

Cited by 7 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Symbolic AI for XAI: Evaluating LFIT Inductive Programming for Explaining Biases in Machine Learning;Computers;2021-11-17

2. An Ant Colony Optimization approach for symbolic regression using Straight Line Programs. Application to energy consumption modelling;International Journal of Approximate Reasoning;2020-06

3. Straight line programs for energy consumption modelling;Applied Soft Computing;2019-07

4. A Comparison Between NARX Neural Networks and Symbolic Regression: An Application for Energy Consumption Forecasting;Communications in Computer and Information Science;2018

5. Experimental Evaluation of Straight Line Programs for Hydrological Modelling with Exogenous Variables;Lecture Notes in Computer Science;2017