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GECCO
2006
Springer
150views Optimization» more  GECCO 2006»
13 years 11 months ago
Nonlinear parametric regression in genetic programming
Genetic programming has been considered a promising approach for function approximation since it is possible to optimize both the functional form and the coefficients. However, it...
Yung-Keun Kwon, Sung-Soon Choi, Byung Ro Moon
GECCO
2004
Springer
14 years 1 months ago
Multi-agent Cooperation Using Genetic Network Programming with Automatically Defined Groups
In this paper, we propose a genetic network programming (GNP) architecture using a coevolution model called automatically defined groups (ADG). The GNP evolves networks for describ...
Tadahiko Murata, Takashi Nakamura
GECCO
2009
Springer
156views Optimization» more  GECCO 2009»
14 years 2 months ago
Characterizing the genetic programming environment for fifth (GPE5) on a high performance computing cluster
Solving complex, real-world problems with genetic programming (GP) can require extensive computing resources. However, the highly parallel nature of GP facilitates using a large n...
Kenneth Holladay
GPEM
2002
145views more  GPEM 2002»
13 years 7 months ago
An Analysis of the Causes of Code Growth in Genetic Programming
Abstract. This research examines the cause of code growth (bloat) in genetic programming (GP). Currently there are three hypothesized causes of code growth in GP: protection, drift...
Terence Soule, Robert B. Heckendorn