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GECCO
2004
Springer
155views Optimization» more  GECCO 2004»
14 years 1 months ago
Genetic Network Programming with Reinforcement Learning and Its Performance Evaluation
A new graph-based evolutionary algorithm named “Genetic Network Programming, GNP” has been proposed. GNP represents its solutions as directed graph structures, which can improv...
Shingo Mabu, Kotaro Hirasawa, Jinglu Hu
UPP
2004
Springer
14 years 1 months ago
Inverse Design of Cellular Automata by Genetic Algorithms: An Unconventional Programming Paradigm
Evolving solutions rather than computing them certainly represents an unconventional programming approach. The general methodology of evolutionary computation has already been know...
Thomas Bäck, Ron Breukelaar, Lars Willmes
EUROGP
2009
Springer
132views Optimization» more  EUROGP 2009»
14 years 2 months ago
A Statistical Learning Perspective of Genetic Programming
Code bloat, the excessive increase of code size, is an important issue in Genetic Programming (GP). This paper proposes a theoretical analysis of code bloat in GP from the perspec...
Nur Merve Amil, Nicolas Bredeche, Christian Gagn&e...
IWVF
2001
Springer
14 years 3 days ago
Grouping Character Shapes by Means of Genetic Programming
In the framework of an evolutionary approach to machine learning, this paper presents the preliminary version of a learning system that uses Genetic Programming as a tool for autom...
Claudio De Stefano, Antonio Della Cioppa, Angelo M...
GECCO
2009
Springer
130views Optimization» more  GECCO 2009»
14 years 8 days ago
Neutrality and variability: two sides of evolvability in linear genetic programming
The notion of evolvability has been put forward to describe the“core mechanism”of natural and artificial evolution. Recently, studies have revealed the influence of the envi...
Ting Hu, Wolfgang Banzhaf