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EVOW
1994
Springer
13 years 11 months ago
Genetic Approaches to Learning Recursive Relations
The genetic programming (GP) paradigm is a new approach to inductively forming programs that describe a particular problem. The use of natural selection based on a fitness ]unction...
Peter A. Whigham, Robert I. McKay
TREC
2003
13 years 9 months ago
Ranking Function Discovery by Genetic Programming for Robust Retrieval
Ranking functions are instrumental for the success of an information retrieval (search engine) system. However nearly all existing ranking functions are manually designed based on...
Li Wang, Weiguo Fan, Rui Yang, Wensi Xi, Ming Luo,...
GECCO
2004
Springer
14 years 29 days ago
Multi-branches Genetic Programming as a Tool for Function Approximation
This work presents a performance analysis of a Multi-Branches Genetic Programming (MBGP) approach applied in symbolic regression (e.g. function approximation) problems. Genetic Pro...
Katya Rodríguez-Vázquez, Carlos Oliv...
ICMLA
2007
13 years 9 months ago
Improving gene expression programming performance by using differential evolution
Gene Expression Programming (GEP) is an evolutionary algorithm that incorporates both the idea of a simple, linear chromosome of fixed length used in Genetic Algorithms (GAs) and...
Qiongyun Zhang, Chi Zhou, Weimin Xiao, Peter C. Ne...
GECCO
2005
Springer
14 years 1 months ago
Probing for limits to building block mixing with a tunably-difficult problem for genetic programming
This paper describes a tunably-difficult problem for genetic programming (GP) that probes for limits to building block mixing and assembly. The existence of such a problem can be ...
Jason M. Daida, Michael E. Samples, Matthew J. Byo...