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GECCO
2004
Springer
103views Optimization» more  GECCO 2004»
14 years 23 days ago
Training Neural Networks with GA Hybrid Algorithms
Abstract. Training neural networks is a complex task of great importance in the supervised learning field of research. In this work we tackle this problem with five algorithms, a...
Enrique Alba, J. Francisco Chicano
GECCO
2000
Springer
13 years 11 months ago
Modeling GA Performance for Control Parameter Optimization
Optimization of the control parameters of genetic algorithms is often a time consuming and tedious task. In this work we take the meta-level genetic algorithm approach to control ...
Vincent A. Cicirello, Stephen F. Smith
IJON
2006
127views more  IJON 2006»
13 years 7 months ago
Evolved neural networks based on cellular automata for sensory-motor controller
Constructing the controller of a mobile robot has several issues to be addressed: how to automate behavior generation procedure, how to insert available domain knowledge effective...
Kyung-Joong Kim, Sung-Bae Cho
ICONIP
1998
13 years 8 months ago
ECOS: Evolving Connectionist Systems and the ECO Learning Paradigm
The paper presents a framework called ECOS for Evolving COnnectionist Systems. ECOS evolve through incremental learning. They can accommodate any new input data, including new fea...
Nikola K. Kasabov
IJCAI
1997
13 years 8 months ago
Evolvable Hardware for Generalized Neural Networks
This paper describes an evolvable hardware (EHW) system for generalized neural network learning. We have developed an ASIC VLSI chip, which is a building block to configure a scal...
Masahiro Murakawa, Shuji Yoshizawa, Isamu Kajitani...