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GECCO
2009
Springer
113views Optimization» more  GECCO 2009»
13 years 10 months ago
Variable size population for dynamic optimization with genetic programming
A new model of Genetic Programming with variable size population is presented in this paper and applied to the reconstruction of target functions in dynamic environments (i.e. pro...
Leonardo Vanneschi, Giuseppe Cuccu
ICML
1994
IEEE
13 years 8 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
GECCO
2007
Springer
200views Optimization» more  GECCO 2007»
13 years 11 months ago
Adaptive genetic programming for option pricing
Genetic Programming (GP) is an automated computational programming methodology, inspired by the workings of natural evolution techniques. It has been applied to solve complex prob...
Zheng Yin, Anthony Brabazon, Conall O'Sullivan
GECCO
2004
Springer
140views Optimization» more  GECCO 2004»
13 years 10 months ago
Keeping the Diversity with Small Populations Using Logic-Based Genetic Programming
We present a new method of Logic-Based Genetic Programming (LBGP). Using the intrinsic mechanism of backtracking in Prolog, we utilize large individual programs with redundant clau...
Ken Taniguchi, Takao Terano
GECCO
2005
Springer
136views Optimization» more  GECCO 2005»
13 years 10 months ago
Preventing overfitting in GP with canary functions
Overfitting is a fundamental problem of most machine learning techniques, including genetic programming (GP). Canary functions have been introduced in the literature as a concept ...
Nate Foreman, Matthew P. Evett