Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/24848
Appears in Collections:Computing Science and Mathematics Conference Papers and Proceedings
Peer Review Status: Refereed
Author(s): Langdon, William B
Veerapen, Nadarajen
Ochoa, Gabriela
Contact Email: nve@cs.stir.ac.uk
Title: Visualising the Search Landscape of the Triangle Program
Editor(s): McDermott, J
Castelli, M
Sekanina, L
Haasdijk, E
García-Sánchez, P
Citation: Langdon WB, Veerapen N & Ochoa G (2017) Visualising the Search Landscape of the Triangle Program. In: McDermott J, Castelli M, Sekanina L, Haasdijk E & García-Sánchez P (eds.) EuroGP 2017: Genetic Programming. Lecture Notes in Computer Science, 10196. The 20th European Conference on Genetic Programming (EuroGP), Amsterdam, The Netherlands, 19.04.2017-21.04.2017. Cham, Switzerland: Springer, pp. 96-113. https://doi.org/10.1007/978-3-319-55696-3_7
Issue Date: 2017
Date Deposited: 23-Jan-2017
Series/Report no.: Lecture Notes in Computer Science, 10196
Conference Name: The 20th European Conference on Genetic Programming (EuroGP)
Conference Dates: 2017-04-19 - 2017-04-21
Conference Location: Amsterdam, The Netherlands
Abstract: High order mutation analysis of a software engineering benchmark, including schema and local optima networks, suggests program improvements may not be as hard to find as is often assumed. 1) Bit-wise genetic building blocks are not deceptive and can lead to all global optima. 2) There are many neutral networks, plateaux and local optima, nevertheless in most cases near the human written C source code there are hill climbing routes including neutral moves to solutions.
Status: AM - Accepted Manuscript
Rights: Publisher policy allows this work to be made available in this repository; The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-55696-3_7

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