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Model-based evolutionary algorithms: GECCO 2018 tutorial

Year: 2018

Type: conference-paper

Abstract: ◮ Little known about the structure of the problem ◮ Clean separation optimizer from problem definition ◮ Easy and generally applicable Approach * Classical EAs: need suitable representation & variation operators * Model-Based EAs: learn structure from good solutions

Source: Genetic and Evolutionary Computation Conference Companion (GECCO Companion)

DOI: 10.1145/3205651.3207874

Authors: Dirk Thierens, Peter A. N. Bosman

Institutions: Utrecht University, Centrum Wiskunde & Informatica

Language: English

Topic: Metaheuristic Optimization Algorithms Research

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W2736157094

FWCI:

Cites: 3

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