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» Fitness Clouds and Problem Hardness in Genetic Programming
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TSMC
2008
100views more  TSMC 2008»
13 years 7 months ago
Instruction-Matrix-Based Genetic Programming
In genetic programming (GP), evolving tree nodes separately would reduce the huge solution space. However, tree nodes are highly interdependent with respect to their fitness. In th...
Gang Li, Jin Feng Wang, Kin-Hong Lee, Kwong-Sak Le...
GECCO
2004
Springer
140views Optimization» more  GECCO 2004»
14 years 1 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
EUROGP
2005
Springer
122views Optimization» more  EUROGP 2005»
14 years 1 months ago
Evolution of Robot Controller Using Cartesian Genetic Programming
Abstract. Cartesian Genetic Programming is a graph based representation that has many benefits over traditional tree based methods, including bloat free evolution and faster evolu...
Simon Harding, Julian F. Miller
GECCO
2008
Springer
145views Optimization» more  GECCO 2008»
13 years 8 months ago
Memory with memory: soft assignment in genetic programming
Based in part on observations about the incremental nature of most state changes in biological systems, we introduce the idea of Memory with Memory in Genetic Programming (GP), wh...
Nicholas Freitag McPhee, Riccardo Poli
EUROGP
1999
Springer
13 years 12 months ago
Genetic Programming as a Darwinian Invention Machine
Genetic programming is known to be capable of creating designs that satisfy prespecified high-level design requirements for analog electrical circuits and other complex structures...
John R. Koza, Forrest H. Bennett III, Oscar Stiffe...