Batch tournament selection for genetic programming

Vinícius V. De Melo, Danilo Vasconcellos Vargas, Wolfgang Banzhaf

研究成果: 書籍/レポート タイプへの寄稿会議への寄与

7 被引用数 (Scopus)

抄録

Lexicase selection achieves very good solution quality by introducing ordered test cases. However, the computational complexity of lexicase selection can prohibit its use in many applications. In this paper, we introduce Batch Tournament Selection (BTS), a hybrid of tournament and lexicase selection which is approximately one order of magnitude faster than lexicase selection while achieving a competitive quality of solutions. Tests on a number of regression datasets show that BTS compares well with lexicase selection in terms of mean absolute error while having a speed-up of up to 25 times. Surprisingly, BTS and lexicase selection have almost no difference in both diversity and performance. This reveals that batches and ordered test cases are completely different mechanisms which share the same general principle fostering the specialization of individuals. This work introduces an efficient algorithm that sheds light onto the main principles behind the success of lexicase, potentially opening up a new range of possibilities for algorithms to come.

本文言語英語
ホスト出版物のタイトルGECCO 2019 - Proceedings of the 2019 Genetic and Evolutionary Computation Conference
出版社Association for Computing Machinery, Inc
ページ994-1002
ページ数9
ISBN(電子版)9781450361118
DOI
出版ステータス出版済み - 7月 13 2019
イベント2019 Genetic and Evolutionary Computation Conference, GECCO 2019 - Prague, チェコ共和国
継続期間: 7月 13 20197月 17 2019

出版物シリーズ

名前GECCO 2019 - Proceedings of the 2019 Genetic and Evolutionary Computation Conference

会議

会議2019 Genetic and Evolutionary Computation Conference, GECCO 2019
国/地域チェコ共和国
CityPrague
Period7/13/197/17/19

!!!All Science Journal Classification (ASJC) codes

  • 計算数学

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