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141
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AIEDAM
2008
157views more  AIEDAM 2008»
15 years 3 months ago
Evolutionary synthesis of kinematic mechanisms
This paper discusses the application of genetic programming to the synthesis of compound two-dimensional kinematic mechanisms, and benchmarks the results against one of the classi...
Hod Lipson
164
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GECCO
2009
Springer
164views Optimization» more  GECCO 2009»
15 years 1 months ago
Solving iterated functions using genetic programming
An iterated function f(x) is a function that when composed with itself, produces a given expression f(f(x))=g(x). Iterated functions are essential constructs in fractal theory and...
Michael D. Schmidt, Hod Lipson
173
Voted
GECCO
2009
Springer
148views Optimization» more  GECCO 2009»
15 years 1 months ago
Genetic programming for quantitative stock selection
We provide an overview of using genetic programming (GP) to model stock returns. Our models employ GP terminals (model decision variables) that are financial factors identified by...
Ying L. Becker, Una-May O'Reilly
135
Voted
GECCO
2007
Springer
144views Optimization» more  GECCO 2007»
15 years 7 months ago
The reliability of confidence intervals for computational effort comparisons
This paper analyses the reliability of confidence intervals for Koza's computational effort statistic. First, we conclude that dependence between the observed minimum generat...
Matthew Walker, Howard Edwards, Chris H. Messom
138
Voted
GECCO
2010
Springer
191views Optimization» more  GECCO 2010»
15 years 3 months ago
Fitness importance for online evolution
To complement standard fitness functions, we propose "Fitness Importance" (FI) as a novel meta-heuristic for online learning systems. We define FI and show how it can be...
Philip Valencia, Raja Jurdak, Peter Lindsay