Jul 8, 2009 · We have examined the application of genetic Algorithms to noisy fitness functions and consider the accepted wisdom of sampling, ...
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Fiacc Larkin, Conor Ryan : Avoiding the pitfalls of noisy fitness functions with genetic algorithms. GECCO 2009: 1861-1862.
May 13, 2016 · The fitness function plays a very important role in guiding GA. Good fitness functions will help GA to explore the search space effectively and efficiently.
Genetic Algorithms with Noisy Fitness - ScienceDirect.com
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Abstract-The convergence properties of genetic algorithms with noisy fitness information are studied here. In the proposed scheme, hypothesis testing ...
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The authors discuss optimization of functions with uncertainty by means of genetic algorithms (GAs). In practical application of such GAs, the possible ...
Missing: Avoiding pitfalls
In the present paper, optimization of functions with uncertainty by means of Genetic Algorithms (GA) is discussed. For such problems, there have been ...
Missing: Avoiding pitfalls
Nov 22, 2018 · The fitness function is a way to define the goal of a genetic algorithm. It provides a way to compare how "good" two solutions are.
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We demonstrate the performance of our scheme via a simple function optimization problem using genetic algorithm in a noisy environment. Our results show ...
Missing: Avoiding pitfalls
Apr 24, 2020 · Some of them called it "junk science", and some pointed me to the fact that no one serious CS/AI/ML researchers work on these topics.
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A theoretical model is presented which describes selection in a genetic algorithm (GA) under a stochastic fitness measure and correctly accounts for finite ...