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Chapter

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Title

Improving Genetic Programming with Behavioral Consistency Measure

Authors

[ 1 ] Instytut Informatyki, Wydział Informatyki, Politechnika Poznańska | [ P ] employee

Year of publication

2014

Chapter type

paper

Publication language

english

Keywords
EN
  • program synthesis
  • genetic programming
  • entropy
  • multi-objective search
Abstract

EN Program synthesis tasks usually specify only the desired output of a program and do not state any expectations about its internal behavior. The intermediate execution states reached by a running program can be nonetheless deemed as more or less preferred according to their information content with respect to the desired output. In this paper, a consistency measure is proposed that implements this observation. When used as an additional search objective in a typical genetic programming setting, this measure improves the success rate on a suite of 35 benchmarks in a statistically significant way.

Pages (from - to)

434 - 443

DOI

10.1007/978-3-319-10762-2_43

URL

https://link.springer.com/chapter/10.1007/978-3-319-10762-2_43

Book

Parallel Problem Solving from Nature - PPSN XIII : 13th International Conference, Ljubljana, Slovenia, September 13-17, 2014 : proceedings

Presented on

13th International Conference on Parallel Problem Solving from Nature, PPSN 2014, 13-17.09.2014, Ljubljana, Slovenia

Publication indexed in

WoS (15)

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