Article

Evolutionary online services

Authors:

Alfredo Milani,

Silvia Suriani,

Stefano MarcuginiAuthors Info & Claims

ICEC '05: Proceedings of the 7th international conference on Electronic commerce

Pages 343 - 349

https://doi.org/10.1145/1089551.1089614

Published: 15 August 2005 Publication History

Abstract

This paper present a technique based on genetic algorithms for generating online adaptive services. Online adaptive systems provide flexible services to a mass of clients/users for maximizing some system goals; they dynamically adapt the form and the content of the issued services while the population of clients evolve over time. The idea of online genetic algorithms (online GAs) is to use the online clients response behavior as a fitness function in order to produce the next generation of services. The principle implemented in online GAs, "the application environment is the fitness", allow to model highly evolutionary domains where both services providers and clients change and evolve over time. The flexibility and the adaptive behavior of this approach seems to be very relevant and promising for applications characterized by highly dynamical features such as in the web domain (online newspapers, e-markets, websites and advertising engines). Nevertheless the proposed technique has a more general aim for application environments characterized by a massive number of anonymous clients/users which require personalized services, such as in the case of many new IT applications.

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Cited By

Tejeda-Ocampo CLópez-Cuevas ATerashima-Marin H(2020)Improving Deep Interactive Evolution with a Style-Based Generator for Artistic Expression and Creative ExplorationEntropy10.3390/e2301001123:1(11)Online publication date: 24-Dec-2020
https://doi.org/10.3390/e23010011

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cover image ACM Other conferences

ICEC '05: Proceedings of the 7th international conference on Electronic commerce

August 2005

957 pages

ISBN:1595931120

DOI:10.1145/1089551

Conference Chairs:
Qi Li
Xi'an Jiaotong University, China
,
Ting-Peng Liang
Sun Yat-Sen University, Taiwan, China

Copyright © 2005 ACM.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 15 August 2005

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Cited By

Tejeda-Ocampo CLópez-Cuevas ATerashima-Marin H(2020)Improving Deep Interactive Evolution with a Style-Based Generator for Artistic Expression and Creative ExplorationEntropy10.3390/e2301001123:1(11)Online publication date: 24-Dec-2020
https://doi.org/10.3390/e23010011

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