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146
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FOGA
1990
15 years 4 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
117
Voted
FOGA
2007
15 years 5 months ago
Neighborhood Graphs and Symmetric Genetic Operators
In the case where the search space has a group structure, classical genetic operators (mutation and two-parent crossover) which respect the group action are completely characterize...
Jonathan E. Rowe, Michael D. Vose, Alden H. Wright
116
Voted
FOGA
1998
15 years 5 months ago
Schemata as Building Blocks: Does Size Matter?
We analyze the schema theorem and the building block hypothesis using a recently derived, exact schemata evolution equation. We derive a new schema theorem based on the concept of...
Christopher R. Stephens, Henri Waelbroeck, R. Agui...
125
Voted
FOGA
1996
15 years 5 months ago
Real Representations
This paper introduces two new representations for real-parameter spaces--the Dedekind and Isodedekind representations. Point mutation and uniform crossover--in their generalised, ...
Patrick D. Surry, Nicholas J. Radcliffe
122
Voted
FOGA
1994
15 years 5 months ago
Predictive Models Using Fitness Distributions of Genetic Operators
An important goal of the theory of genetic algorithms is to build predictive models of how well genetic algorithms are expected to perform, given a representation, a fitness lands...
John J. Grefenstette