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GECCO
2000
Springer
101views Optimization» more  GECCO 2000»
13 years 8 months ago
Characterizing a Tunably Difficult Problem in Genetic Programming
This paper examines the behavioral phenomena that occur with the tuning of the binomial-3 problem. Our analysis identifies a distinct set of phenomena that may be generalizable to...
Omer A. Chaudhri, Jason M. Daida, Jonathan C. Khoo...
GECCO
2003
Springer
13 years 10 months ago
What Makes a Problem GP-Hard? Validating a Hypothesis of Structural Causes
Abstract. This paper provides an empirical test of a hypothesis, which describes the effects of structural mechanisms in genetic programming. In doing so, the paper offers a test p...
Jason M. Daida, Hsiaolei Li, Ricky Tang, Adam M. H...
FLAIRS
2006
13 years 6 months ago
Genetic Programming: Analysis of Optimal Mutation Rates in a Problem with Varying Difficulty
In this paper we test whether a correlation exists between the optimal mutation rate and problem difficulty. We find that the range of optimal mutation rates is inversely proporti...
Alan Piszcz, Terence Soule
GECCO
2009
Springer
156views Optimization» more  GECCO 2009»
13 years 11 months ago
Characterizing the genetic programming environment for fifth (GPE5) on a high performance computing cluster
Solving complex, real-world problems with genetic programming (GP) can require extensive computing resources. However, the highly parallel nature of GP facilitates using a large n...
Kenneth Holladay
FGCS
2010
119views more  FGCS 2010»
13 years 3 months ago
Characterizing fault tolerance in genetic programming
Evolutionary Algorithms, including Genetic Programming (GP), are frequently employed to solve difficult real-life problems, which can require up to days or months of computation. ...
Daniel Lombraña Gonzalez, Francisco Fern&aa...