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Authors: Neil Crossley ; Emanuel Kitzelmann ; Martin Hofmann and Ute Schmid

Affiliation: University of Bamberg, Germany

Keyword(s): Recursive functions, Analytical inductive programming, Evolutionary programming.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Artificial Life ; Computational Intelligence ; Evolutionary Computing ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Machine Learning ; Soft Computing ; Symbolic Systems

Abstract: Evolutionary programming is the most powerful method for inducing recursive functional programs from input/output examples while taking into account efficiency and complexity constraints for the target program. However, synthesis time can be considerably high. A strategy which is complementary to the generate-and -test based approaches of evolutionary programming is inductive analytical programming where program construction is example-driven, that is, target programs are constructed as minimal generalization over the given input/output examples. Synthesis with analytical approaches is fast, but the scope of synthesizable programs is restricted. We propose to combine both approaches in such a way that the power of evolutionary programming is preserved and synthesis becomes more efficient. We use the analytical system IGOR2 to generate seeds in form of program skeletons to guide the evolutionary system ADATE when searching for target programs. In an evaluations with several examples w e can show that using such seeds indeed can speed up evolutionary programming considerably. (More)

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Paper citation in several formats:
Crossley, N.; Kitzelmann, E.; Hofmann, M. and Schmid, U. (2009). EVOLUTIONARY PROGRAMMING GUIDED BY ANALYTICALLY GENERATED SEEDS. In Proceedings of the International Joint Conference on Computational Intelligence (IJCCI 2009) - ICEC; ISBN 978-989-674-014-6; ISSN 2184-3236, SciTePress, pages 197-202. DOI: 10.5220/0002286301970202

@conference{icec09,
author={Neil Crossley. and Emanuel Kitzelmann. and Martin Hofmann. and Ute Schmid.},
title={EVOLUTIONARY PROGRAMMING GUIDED BY ANALYTICALLY GENERATED SEEDS},
booktitle={Proceedings of the International Joint Conference on Computational Intelligence (IJCCI 2009) - ICEC},
year={2009},
pages={197-202},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002286301970202},
isbn={978-989-674-014-6},
issn={2184-3236},
}

TY - CONF

JO - Proceedings of the International Joint Conference on Computational Intelligence (IJCCI 2009) - ICEC
TI - EVOLUTIONARY PROGRAMMING GUIDED BY ANALYTICALLY GENERATED SEEDS
SN - 978-989-674-014-6
IS - 2184-3236
AU - Crossley, N.
AU - Kitzelmann, E.
AU - Hofmann, M.
AU - Schmid, U.
PY - 2009
SP - 197
EP - 202
DO - 10.5220/0002286301970202
PB - SciTePress

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