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GECCO
2007
Springer
183views Optimization» more  GECCO 2007»
15 years 11 months ago
Distribution replacement: how survival of the worst can out perform survival of the fittest
A new family of "Distribution Replacement” operators for use in steady state genetic algorithms is presented. Distribution replacement enforces the members of the populatio...
Howard Tripp, Phil Palmer
CRV
2006
IEEE
137views Robotics» more  CRV 2006»
15 years 11 months ago
Evolving a Vision-Based Line-Following Robot Controller
This paper presents an original framework for evolving a vision-based mobile robot controller using genetic programming. This framework is built on the Open BEAGLE framework for t...
Jean-François Dupuis, Marc Parizeau
MFCS
2004
Springer
15 years 10 months ago
Approximating Boolean Functions by OBDDs
In learning theory and genetic programming, OBDDs are used to represent approximations of Boolean functions. This motivates the investigation of the OBDD complexity of approximatin...
Andre Gronemeier
154
Voted
EH
2003
IEEE
129views Hardware» more  EH 2003»
15 years 10 months ago
The Importance of Reuse and Development in Evolvable Hardware
Reuse will become increasingly important as larger digital and analog circuits are created by the techniques of the field of evolvable hardware. This paper discusses the ways by w...
John R. Koza, Martin A. Keane, Matthew J. Streeter
GECCO
2009
Springer
258views Optimization» more  GECCO 2009»
15 years 9 months ago
Evolutionary learning of local descriptor operators for object recognition
Nowadays, object recognition is widely studied under the paradigm of matching local features. This work describes a genetic programming methodology that synthesizes mathematical e...
Cynthia B. Pérez, Gustavo Olague