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» Unsupervised Problem Decomposition Using Genetic Programming
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GECCO
2009
Springer
134views Optimization» more  GECCO 2009»
15 years 2 months ago
Estimating the distribution and propagation of genetic programming building blocks through tree compression
Shin et al [19] and McKay et al [15] previously applied tree compression and semantics-based simplification to study the distribution of building blocks in evolving Genetic Progr...
Robert I. McKay, Xuan Hoai Nguyen, James R. Cheney...
GECCO
2005
Springer
110views Optimization» more  GECCO 2005»
15 years 3 months ago
Towards identifying populations that increase the likelihood of success in genetic programming
This paper presents a comprehensive, multivariate account of how initial population material is used over the course of a genetic programming run as while various factors influenc...
Jason M. Daida
ICML
1994
IEEE
15 years 1 months ago
Hierarchical Self-Organization in Genetic programming
This paper presents an approach to automatic discovery of functions in Genetic Programming. The approach is based on discovery of useful building blocks by analyzing the evolution...
Justinian P. Rosca, Dana H. Ballard
EUROGP
2001
Springer
103views Optimization» more  EUROGP 2001»
15 years 2 months ago
Computational Complexity, Genetic Programming, and Implications
Recent theory work has shown that a Genetic Program (GP) used to produce programs may have output that is bounded above by the GP itself [l]. This paper presents proofs that show t...
Bart Rylander, Terence Soule, James A. Foster
GECCO
2005
Springer
136views Optimization» more  GECCO 2005»
15 years 3 months ago
Multi-chromosomal genetic programming
This paper introduces an evolutionary algorithm which uses multiple chromosomes to evolve solutions to a symbolic regression problem. Inspiration for this algorithm is provided by...
Rachel Cavill, Stephen L. Smith, Andrew M. Tyrrell