Theory of estimation-of-distribution algorithms

Carsten Witt

doi:10.1145/3205651.3207890

Theory of estimation-of-distribution algorithms

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

Abstract

Summary Runtime analysis for simple univariate EDAs Identified similarities to and differences from simple EAs Genetic drift a major obstacle Sensitive to parameters (phase transitions) Robust to noise Significance-based EDAs as novel theory-driven approach Future work Combinatorial problems Multivariate EDAs Classification of problems w. r. t. appropriateness for EAs/EDAs.

Original language	English
Title of host publication	Proceedings of the Genetic and Evolutionary Computation Conference Companion
Publisher	Association for Computing Machinery
Publication date	2018
Pages	1170-1197
ISBN (Print)	978-1-4503-5764-7
DOIs	https://doi.org/10.1145/3205651.3207890
Publication status	Published - 2018
Event	2018 Genetic and Evolutionary Computation Conference - Kyoto Terrsa, Kyoto, Japan Duration: 15 Jul 2018 → 19 Jul 2018

Conference

Conference	2018 Genetic and Evolutionary Computation Conference
Location	Kyoto Terrsa
Country	Japan
City	Kyoto
Period	15/07/2018 → 19/07/2018

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10.1145/3205651.3207890

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title = "Theory of estimation-of-distribution algorithms",

abstract = "Summary Runtime analysis for simple univariate EDAs Identified similarities to and differences from simple EAs Genetic drift a major obstacle Sensitive to parameters (phase transitions) Robust to noise Significance-based EDAs as novel theory-driven approach Future work Combinatorial problems Multivariate EDAs Classification of problems w. r. t. appropriateness for EAs/EDAs.",

author = "Carsten Witt",

year = "2018",

doi = "10.1145/3205651.3207890",

language = "English",

isbn = "978-1-4503-5764-7",

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booktitle = "Proceedings of the Genetic and Evolutionary Computation Conference Companion",

publisher = "Association for Computing Machinery",

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note = "2018 Genetic and Evolutionary Computation Conference, GECCO 2018 ; Conference date: 15-07-2018 Through 19-07-2018",

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AB - Summary Runtime analysis for simple univariate EDAs Identified similarities to and differences from simple EAs Genetic drift a major obstacle Sensitive to parameters (phase transitions) Robust to noise Significance-based EDAs as novel theory-driven approach Future work Combinatorial problems Multivariate EDAs Classification of problems w. r. t. appropriateness for EAs/EDAs.

U2 - 10.1145/3205651.3207890

DO - 10.1145/3205651.3207890

M3 - Article in proceedings

SN - 978-1-4503-5764-7

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BT - Proceedings of the Genetic and Evolutionary Computation Conference Companion

PB - Association for Computing Machinery

T2 - 2018 Genetic and Evolutionary Computation Conference

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