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GECCO
2008
Springer
143views Optimization» more  GECCO 2008»
13 years 11 months ago
Enhanced generalized ant programming (EGAP)
This paper begins by reviewing different methods of automatic programming while emphasizing the technique of Ant Programming (AP). AP uses an ant foraging metaphor in which ants g...
Amirali Salehi-Abari, Tony White
GECCO
2008
Springer
120views Optimization» more  GECCO 2008»
13 years 11 months ago
Genetic programming with polymorphic types and higher-order functions
This article introduces our new approach to program representation for genetic programming (GP). We replace the usual s-expression representation scheme by a strongly-typed ion-ba...
Franck Binard, Amy P. Felty
GECCO
2008
Springer
201views Optimization» more  GECCO 2008»
13 years 11 months ago
Advanced techniques for the creation and propagation of modules in cartesian genetic programming
The choice of an appropriate hardware representation model is key to successful evolution of digital circuits. One of the most popular models is cartesian genetic programming, whi...
Paul Kaufmann, Marco Platzner
GECCO
2008
Springer
179views Optimization» more  GECCO 2008»
13 years 11 months ago
Developing neural structure of two agents that play checkers using cartesian genetic programming
A developmental model of neural network is presented and evaluated in the game of Checkers. The network is developed using cartesian genetic programs (CGP) as genotypes. Two agent...
Gul Muhammad Khan, Julian Francis Miller, David M....
GECCO
2010
Springer
191views Optimization» more  GECCO 2010»
13 years 11 months ago
Fitness importance for online evolution
To complement standard fitness functions, we propose "Fitness Importance" (FI) as a novel meta-heuristic for online learning systems. We define FI and show how it can be...
Philip Valencia, Raja Jurdak, Peter Lindsay