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» Fitness Sharing in Genetic Programming
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CEC
2010
IEEE
12 years 11 months ago
Tweaking a tower of blocks leads to a TMBL: Pursuing long term fitness growth in program evolution
— If a population of programs evolved not for a few hundred generations but for a few hundred thousand or more, could it generate more interesting behaviours and tackle more comp...
Tony E. Lewis, George D. Magoulas
IWCLS
2007
Springer
14 years 1 months ago
On Lookahead and Latent Learning in Simple LCS
Learning Classifier Systems use evolutionary algorithms to facilitate rule- discovery, where rule fitness is traditionally payoff based and assigned under a sharing scheme. Most c...
Larry Bull
GECCO
2010
Springer
191views Optimization» more  GECCO 2010»
13 years 7 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
GECCO
2007
Springer
183views Optimization» more  GECCO 2007»
14 years 1 months ago
Genetic programming for cross-task knowledge sharing
We consider multitask learning of visual concepts within genetic programming (GP) framework. The proposed method evolves a population of GP individuals, with each of them composed...
Wojciech Jaskowski, Krzysztof Krawiec, Bartosz Wie...
GECCO
2006
Springer
150views Optimization» more  GECCO 2006»
13 years 11 months ago
Nonlinear parametric regression in genetic programming
Genetic programming has been considered a promising approach for function approximation since it is possible to optimize both the functional form and the coefficients. However, it...
Yung-Keun Kwon, Sung-Soon Choi, Byung Ro Moon