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» Evolutionary algorithms and dynamic programming
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GECCO
2005
Springer
159views Optimization» more  GECCO 2005»
14 years 15 days ago
Using evolutionary algorithms for the unit testing of object-oriented software
As the paradigm of object orientation becomes more and more important for modern IT development projects, the demand for an automated test case generation to dynamically test obje...
Stefan Wappler, Frank Lammermann
DMIN
2006
126views Data Mining» more  DMIN 2006»
13 years 8 months ago
Comparison and Analysis of Mutation-based Evolutionary Algorithms for ANN Parameters Optimization
Mutation-based Evolutionary Algorithms, also known as Evolutionary Programming (EP) are commonly applied to Artificial Neural Networks (ANN) parameters optimization. This paper pre...
Kristina Davoian, Alexander Reichel, Wolfram-Manfr...
CAIP
2009
Springer
200views Image Analysis» more  CAIP 2009»
14 years 1 months ago
Real-Time Stereo Vision: Making More Out of Dynamic Programming
Abstract. Dynamic Programming (DP) is a popular and efficient method for calculating disparity maps from stereo images. It allows for meeting real-time constraints even on low-cos...
Jan Salmen, Marc Schlipsing, Johann Edelbrunner, S...
GECCO
2005
Springer
159views Optimization» more  GECCO 2005»
14 years 15 days ago
Resource-limited genetic programming: the dynamic approach
Resource-Limited Genetic Programming is a bloat control technique that imposes a single limit on the total amount of resources available to the entire population, where resources ...
Sara Silva, Ernesto Costa
GECCO
2005
Springer
158views Optimization» more  GECCO 2005»
14 years 15 days ago
Transition models as an incremental approach for problem solving in evolutionary algorithms
This paper proposes an incremental approach for building solutions using evolutionary computation. It presents a simple evolutionary model called a Transition model in which parti...
Anne Defaweux, Tom Lenaerts, Jano I. van Hemert, J...