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GECCO
2004
Springer
155views Optimization» more  GECCO 2004»
15 years 3 months ago
Genetic Network Programming with Reinforcement Learning and Its Performance Evaluation
A new graph-based evolutionary algorithm named “Genetic Network Programming, GNP” has been proposed. GNP represents its solutions as directed graph structures, which can improv...
Shingo Mabu, Kotaro Hirasawa, Jinglu Hu
CINQ
2004
Springer
116views Database» more  CINQ 2004»
15 years 1 months ago
Contribution to Gene Expression Data Analysis by Means of Set Pattern Mining
Abstract. One of the exciting scientific challenges in functional genomics concerns the discovery of biologically relevant patterns from gene expression data. For instance, it is e...
Ruggero G. Pensa, Jérémy Besson, C&e...
GECCO
2010
Springer
233views Optimization» more  GECCO 2010»
15 years 2 months ago
Evolutionary-based conflict-free scheduling of collective communications on spidergon NoCs
The Spidergon interconnection network has become popular recently in multiprocessor systems on chips. To the best of our knowledge, algorithms for collective communications (CC) h...
Jirí Jaros, Vaclav Dvorak
GECCO
2007
Springer
156views Optimization» more  GECCO 2007»
15 years 3 months ago
Techniques for highly multiobjective optimisation: some nondominated points are better than others
The research area of evolutionary multiobjective optimization (EMO) is reaching better understandings of the properties and capabilities of EMO algorithms, and accumulating much e...
David W. Corne, Joshua D. Knowles
GECCO
2007
Springer
155views Optimization» more  GECCO 2007»
15 years 3 months ago
Solving the MAXSAT problem using a multivariate EDA based on Markov networks
Markov Networks (also known as Markov Random Fields) have been proposed as a new approach to probabilistic modelling in Estimation of Distribution Algorithms (EDAs). An EDA employ...
Alexander E. I. Brownlee, John A. W. McCall, Deryc...