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» On the Brittleness of Evolutionary Algorithms
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EUSFLAT
2009
156views Fuzzy Logic» more  EUSFLAT 2009»
15 years 4 months ago
Interactive Fuzzy Modeling by Evolutionary Multiobjective Optimization with User Preference
One of the new trends in genetic fuzzy systems (GFS) is the use of evolutionary multiobjective optimization (EMO) algorithms. This is because EMO algorithms can easily handle two c...
Yusuke Nojima, Hisao Ishibuchi
CEC
2008
IEEE
16 years 27 days ago
Creating edge detectors by evolutionary reinforcement learning
— In this article we present results from experiments where a edge detector was learned from scratch by EANT2, a method for evolutionary reinforcement learning. The detector is c...
Nils T. Siebel, Sven Grünewald, Gerald Sommer
AE
2007
Springer
16 years 18 days ago
Searching for Glider Guns in Cellular Automata: Exploring Evolutionary and Other Techniques
Abstract. We aim to construct an automatic system for the discovery of collision-based universal cellular automata that simulate Turing machines in their space-time dynamics using ...
Emmanuel Sapin, Larry Bull
DATE
2005
IEEE
172views Hardware» more  DATE 2005»
16 years 1 days ago
Evolutionary Optimization in Code-Based Test Compression
We provide a general formulation for the code-based test compression problem with fixed-length input blocks and propose a solution approach based on Evolutionary Algorithms. In c...
Ilia Polian, Alejandro Czutro, Bernd Becker
FCCM
2005
IEEE
124views VLSI» more  FCCM 2005»
16 years 1 days ago
Parallel Hardware Implementation of Cellular Learning Automata Based Evolutionary Computing (CLA-EC) on FPGA
The CLA-EC is a model obtained by combining the concepts of cellular learning automata and evolutionary algorithms. The parallel structure of the CLA-EC makes it suitable for hard...
Arash Hariri, Reza Rastegar, Morteza Saheb Zamani,...