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GECCO
2010
Springer
150views Optimization» more  GECCO 2010»
15 years 11 months ago
Towards drift correction in chemical sensors using an evolutionary strategy
Gas chemical sensors are strongly affected by the so-called drift, i.e., changes in sensors’ response caused by poisoning and aging that may significantly spoil the measures g...
Stephano Di Carlo, Ernesto Sánchez, Alberto...
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GECCO
2010
Springer
168views Optimization» more  GECCO 2010»
15 years 11 months ago
On the generality of parameter tuning in evolutionary planning
Divide-and-Evolve (DaE) is an original “memeticization” of Evolutionary Computation and Artificial Intelligence Planning. However, like any Evolutionary Algorithm, DaE has se...
Jacques Bibai, Pierre Savéant, Marc Schoena...
GECCO
2010
Springer
178views Optimization» more  GECCO 2010»
15 years 11 months ago
Crossing the reality gap in evolutionary robotics by promoting transferable controllers
The reality gap, that often makes controllers evolved in simulation inefficient once transferred onto the real system, remains a critical issue in Evolutionary Robotics (ER); it p...
Sylvain Koos, Jean-Baptiste Mouret, Stéphan...
GECCO
2009
Springer
162views Optimization» more  GECCO 2009»
15 years 11 months ago
On the appropriateness of evolutionary rule learning algorithms for malware detection
In this paper, we evaluate the performance of ten well-known evolutionary and non-evolutionary rule learning algorithms. The comparative study is performed on a real-world classi...
M. Zubair Shafiq, S. Momina Tabish, Muddassar Faro...
CEC
2007
IEEE
15 years 10 months ago
Efficient relevance estimation and value calibration of evolutionary algorithm parameters
Calibrating the parameters of an evolutionary algorithm (EA) is a laborious task. The highly stochastic nature of an EA typically leads to a high variance of the measurements. The ...
Volker Nannen, A. E. Eiben