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GECCO
2000
Springer
138views Optimization» more  GECCO 2000»
15 years 1 months ago
Time Complexity of genetic algorithms on exponentially scaled problems
This paper gives a theoretical and empirical analysis of the time complexity of genetic algorithms (GAs) on problems with exponentially scaled building blocks. It is important to ...
Fernando G. Lobo, David E. Goldberg, Martin Pelika...
ICTAI
1997
IEEE
15 years 1 months ago
GA-Based Performance Analysis of Network Protocols
This paper tackles the problem of analyzing the correctness and performance of a computer network protocol. Given the complexity of the problem, no currently used technique is abl...
Mario Baldi, Fulvio Corno, Maurizio Rebaudengo, Gi...
ICML
2008
IEEE
15 years 10 months ago
An analysis of linear models, linear value-function approximation, and feature selection for reinforcement learning
We show that linear value-function approximation is equivalent to a form of linear model approximation. We then derive a relationship between the model-approximation error and the...
Ronald Parr, Lihong Li, Gavin Taylor, Christopher ...
ARCS
2012
Springer
13 years 5 months ago
Fast Scenario-Based Design Space Exploration using Feature Selection
: This paper presents a novel approach to efficiently perform early system level design space exploration (DSE) of MultiProcessor System-on-Chip (MPSoC) based embedded systems. By...
Peter van Stralen, Andy D. Pimentel
KES
1999
Springer
15 years 2 months ago
Dynamic Demes parallel genetic algorithm
Abstract—Dynamic Demes is a new method for the parallelisation of evolutionary algorithms. It was derived as a combination of two other parallelisation algorithms: the master-sla...
Mariusz Nowostawski, Riccardo Poli