Tournament versus Fitness Uniform Selection

Tournament versus Fitness Uniform Selection

In evolutionary algorithms a critical parameter that must be tuned is that of selection pressure. If it is set too low then the rate of convergence towards the optimum is likely to be slow. Alternatively if the selection pressure is set too high the system is likely to become stuck in a local optimu...

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Bibliographic Details
Main Authors: LEGG, Shane, HUTTER, Marcus, KUMAR, Akshat
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2004
Subjects:
Selection schemes
fitness evaluation
optimization
fitness landscapes
basic working principles of evolutionary computations
(self)adaptation
evolutionary algorithm
deceptive & multimodal optimization problems.
Artificial Intelligence and Robotics
Numerical Analysis and Scientific Computing
Online Access:https://ink.library.smu.edu.sg/sis_research/2217
https://ink.library.smu.edu.sg/context/sis_research/article/3217/viewcontent/Tournament_versus_Fitness_Uniform_Selection.pdf
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Institution: Singapore Management University
Language: English
Description
Summary:In evolutionary algorithms a critical parameter that must be tuned is that of selection pressure. If it is set too low then the rate of convergence towards the optimum is likely to be slow. Alternatively if the selection pressure is set too high the system is likely to become stuck in a local optimum due to a loss of diversity in the population. The recent Fitness Uniform Selection Scheme (FUSS) is a conceptually simple but somewhat radical approach to addressing this problem - rather than biasing the selection towards higher fitness, FUSS biases selection towards sparsely populated fitness levels. In this paper we compare the relative performance of FUSS with the well known tournament selection scheme on a range of problems.

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