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GECCO
2009
Springer
13 years 9 months ago
Binary representation in gene expression programming: towards a better scalability
Jose Garcia Moreno-Torres, Xavier Llorà, Da...
GECCO
2009
Springer
162views Optimization» more  GECCO 2009»
13 years 9 months ago
TestFul: using a hybrid evolutionary algorithm for testing stateful systems
This paper introduces TestFul, a framework for testing stateful systems and focuses on object-oriented software. TestFul employs a hybrid multi-objective evolutionary algorithm, t...
Matteo Miraz, Pier Luca Lanzi, Luciano Baresi
GECCO
2009
Springer
209views Optimization» more  GECCO 2009»
13 years 9 months ago
MC/DC automatic test input data generation
Zeina Awedikian, Kamel Ayari, Giuliano Antoniol
GECCO
2009
Springer
121views Optimization» more  GECCO 2009»
13 years 9 months ago
Using memetic algorithms to improve portfolio performance in static and dynamic trading scenarios
The Portfolio Optimization problem consists of the selection of a group of assets to a long-term fund in order to minimize the risk and maximize the return of the investment. This...
Claus de Castro Aranha, Hitoshi Iba
GECCO
2009
Springer
108views Optimization» more  GECCO 2009»
13 years 9 months ago
Development of combinational circuits using non-uniform cellular automata: initial results
A non-uniform cellular automata-based model is presented for the evolutionary development of digital circuits at the gate level. The main feature of this model is the modified lo...
Michal Bidlo, Zdenek Vasícek
GECCO
2009
Springer
110views Optimization» more  GECCO 2009»
13 years 9 months ago
EMO shines a light on the holes of complexity space
Typical domains used in machine learning analyses only partially cover the complexity space, remaining a large proportion of problem difficulties that are not tested. Since the ac...
Núria Macià, Albert Orriols-Puig, Es...
GECCO
2009
Springer
13 years 9 months ago
The sensitivity of HyperNEAT to different geometric representations of a problem
HyperNEAT, a generative encoding for evolving artificial neural networks (ANNs), has the unique and powerful ability to exploit the geometry of a problem (e.g., symmetries) by enc...
Jeff Clune, Charles Ofria, Robert T. Pennock
GECCO
2009
Springer
128views Optimization» more  GECCO 2009»
13 years 9 months ago
Evolving stochastic processes using feature tests and genetic programming
The synthesis of stochastic processes using genetic programming is investigated. Stochastic process behaviours take the form of time series data, in which quantities of interest v...
Brian J. Ross, Janine H. Imada
GECCO
2009
Springer
134views Optimization» more  GECCO 2009»
13 years 9 months ago
Estimating the distribution and propagation of genetic programming building blocks through tree compression
Shin et al [19] and McKay et al [15] previously applied tree compression and semantics-based simplification to study the distribution of building blocks in evolving Genetic Progr...
Robert I. McKay, Xuan Hoai Nguyen, James R. Cheney...