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GECCO
2009
Springer
112views Optimization» more  GECCO 2009»
14 years 3 months ago
Soft memory for stock market analysis using linear and developmental genetic programming
Recently, a form of memory usage was introduced for genetic programming (GP) called “soft memory.” Rather than have a new value completely overwrite the old value in a registe...
Garnett Carl Wilson, Wolfgang Banzhaf
GECCO
2008
Springer
145views Optimization» more  GECCO 2008»
13 years 10 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
BIOINFORMATICS
2006
106views more  BIOINFORMATICS 2006»
13 years 9 months ago
Identification of biochemical networks by S-tree based genetic programming
Motivation: Most previous approaches to model biochemical networks havefocusedeither on the characterization of a networkstructurewith a number of components or on the estimation ...
Dong-Yeon Cho, Kwang-Hyun Cho, Byoung-Tak Zhang
GECCO
2008
Springer
141views Optimization» more  GECCO 2008»
13 years 10 months ago
Managing team-based problem solving with symbiotic bid-based genetic programming
Bid-based Genetic Programming (GP) provides an elegant mechanism for facilitating cooperative problem decomposition without an a priori specification of the number of team member...
Peter Lichodzijewski, Malcolm I. Heywood
ISCAS
2005
IEEE
179views Hardware» more  ISCAS 2005»
14 years 2 months ago
Robust stabilization of control systems using piecewise linear Lyapunov functions and evolutionary algorithm
— Piecewise linear Lyapunov functions are used to design control gain matrices so that closed systems are robust stable and attractive regions are expanded as large as possible i...
K. Tagawa, Y. Ohta