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FOGA
1990
14 years 11 months ago
A Hierarchical Approach to Learning the Boolean Multiplexer Function
This paper describes the recently developed genetic programming paradigm which genetically breeds populations of computer programs to solve problems. In genetic programming, the i...
John R. Koza
GECCO
2004
Springer
130views Optimization» more  GECCO 2004»
15 years 3 months ago
The Shifting Balance Genetic Algorithm as More than Just Another Island Model GA
The Shifting Balance Genetic Algorithm (SBGA) is an extension of the Genetic Algorithm (GA) that was created to promote guided diversity to improve performance in highly multimodal...
Mark Wineberg, Jun Chen
GECCO
2007
Springer
140views Optimization» more  GECCO 2007»
15 years 3 months ago
Peer-to-peer evolutionary algorithms with adaptive autonomous selection
In this paper we describe and evaluate a fully distributed P2P evolutionary algorithm (EA) with adaptive autonomous selection. Autonomous selection means that decisions regarding ...
W. R. M. U. K. Wickramasinghe, Maarten van Steen, ...
SAC
1998
ACM
15 years 2 months ago
Scalability of an MPI-based fast messy genetic algorithm
The fast messy genetic algorithm (fmGA) belongs to a class of algorithms inspired by the principles of evolution, known appropriately as "evolutionary algorithms" (EAs)....
Laurence D. Merkle, George H. Gates Jr., Gary B. L...
TGC
2007
Springer
15 years 3 months ago
Replicating Web Services for Scalability
Web service instances are often replicated to allow service provision to scale to support larger population sizes of users. However, such systems are difficult to analyse because t...
Mario Bravetti, Stephen Gilmore, Claudio Guidi, Mi...