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» Solving iterated functions using genetic programming
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114
Voted
GECCO
2005
Springer
136views Optimization» more  GECCO 2005»
15 years 9 months ago
Preventing overfitting in GP with canary functions
Overfitting is a fundamental problem of most machine learning techniques, including genetic programming (GP). Canary functions have been introduced in the literature as a concept ...
Nate Foreman, Matthew P. Evett
116
Voted
CEC
2010
IEEE
15 years 4 months ago
Evolving a CUDA kernel from an nVidia template
Rather than attempting to evolve a complete program from scratch we demonstrate genetic interface programming (GIP) by automatically generating a parallel CUDA kernel with identica...
William B. Langdon, Mark Harman
143
Voted
GECCO
2006
Springer
282views Optimization» more  GECCO 2006»
15 years 7 months ago
A genetic algorithm for the longest common subsequence problem
A genetic algorithm for the longest common subsequence problem encodes candidate sequences as binary strings that indicate subsequences of the shortest or first string. Its fitnes...
Brenda Hinkemeyer, Bryant A. Julstrom
156
Voted
EAAI
2010
119views more  EAAI 2010»
15 years 2 months ago
A heuristic-based framework to solve a complex aircraft sizing problem
Aircraft sizing studies consist in determining the main characteristics of an aircraft starting from a set of requirements. These studies can be summarized as global constrained o...
Céline Badufle, Christophe Blondel, Thierry...
136
Voted
GECCO
2005
Springer
155views Optimization» more  GECCO 2005»
15 years 9 months ago
Mission planning for joint suppression of enemy air defenses using a genetic algorithm
In this paper we present a genetic algorithm applied to the problem of mission planning for Joint Suppression of Enemy Air Defenses (JSEAD) in support of air strike operations. Th...
Jeffrey P. Ridder, Jason C. HandUber