Novelty-Organizing Team of Classifiers in noisy and dynamic environments

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

8 被引用数 (Scopus)

抄録

In the real world, the environment is constantly changing with the input variables under the effect of noise. However, few algorithms were shown to be able to work under those circumstances. Here, Novelty-Organizing Team of Classifiers (NOTC) is applied to the continuous action mountain car as well as two variations of it: A noisy mountain car and an unstable weather mountain car. These problems take respectively noise and change of problem dynamics into account. Moreover, NOTC is compared with NeuroEvolution of Augmenting Topologies (NEAT) in these problems, revealing a trade-off between the approaches. While NOTC achieves the best performance in all of the problems, NEAT needs less trials to converge. It is demonstrated that NOTC achieves better performance because of its division of the input space (creating easier problems). Unfortunately, this division of input space also requires a bit of time to bootstrap.

本文言語英語
ホスト出版物のタイトル2015 IEEE Congress on Evolutionary Computation, CEC 2015 - Proceedings
出版社Institute of Electrical and Electronics Engineers Inc.
ページ2937-2944
ページ数8
ISBN(電子版)9781479974924
DOI
出版ステータス出版済み - 9 10 2015
イベントIEEE Congress on Evolutionary Computation, CEC 2015 - Sendai, 日本
継続期間: 5 25 20155 28 2015

出版物シリーズ

名前2015 IEEE Congress on Evolutionary Computation, CEC 2015 - Proceedings

その他

その他IEEE Congress on Evolutionary Computation, CEC 2015
Country日本
CitySendai
Period5/25/155/28/15

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Computational Mathematics

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