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FOGA
1990
15 years 7 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
CP
2007
Springer
15 years 10 months ago
Exploring Different Constraint-Based Modelings for Program Verification
Recently, constraint-programming techniques have been used to generate test data and to verify the conformity of a program with its specification. Constraint generated for these ta...
Hélène Collavizza, Michel Rueher
GECCO
2009
Springer
103views Optimization» more  GECCO 2009»
16 years 15 days ago
Why evolution is not a good paradigm for program induction: a critique of genetic programming
We revisit the roots of Genetic Programming (i.e. Natural Evolution), and conclude that the mechanisms of the process of evolution (i.e. selection, inheritance and variation) are ...
John R. Woodward, Ruibin Bai
STOC
2004
ACM
102views Algorithms» more  STOC 2004»
16 years 6 months ago
A simple polynomial-time rescaling algorithm for solving linear programs
The perceptron algorithm, developed mainly in the machine learning literature, is a simple greedy method for finding a feasible solution to a linear program (alternatively, for le...
John Dunagan, Santosh Vempala
IPPS
2003
IEEE
15 years 11 months ago
Applying Aspect-Orient Programming Concepts to a Component-Based Programming Model
Abstract— The execution environments For scientific applications have evolved significantly over the years. Vector and parallel architectures have provided significantly faste...
Thomas Eidson, Jack Dongarra, Victor Eijkhout