Self-adapting semantic sensitivities for Semantic Similarity based Crossover

Nguyen Quang Uy; Bob McKay; Michael O'Neill; Nguyen Xuan Hoai

doi:10.1109/CEC.2010.5586052

Self-adapting semantic sensitivities for Semantic Similarity based Crossover

Nguyen Quang Uy, Bob McKay, Michael O'Neill, Nguyen Xuan Hoai

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

4 Citations (Scopus)

Abstract

This paper presents two methods for self-adapting the semantic sensitivities in a recently proposed semantics-based crossover: Semantic Similarity based Crossover (SSC) [1]. The first self-adaptation method is inspired by a self-adaptive method for controlling mutation step size in Evolutionary Strategies (1/5 rule). The design of the second takes into account more of our previous experimental observations, that SSC works well only when a certain portion of events successfully exchange semantically similar subtrees. These two proposed methods are then tested on a number of real-valued symbolic regression problems, their performance being compared with SSC using predetermined sensitivities and with standard crossover. The results confirm the benefits of the second self-adaption method.

Original language	English
Title of host publication	2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010
DOIs	https://doi.org/10.1109/CEC.2010.5586052
Publication status	Published - 2010
Externally published	Yes
Event	2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010 - Barcelona, Spain Duration: 18 Jul 2010 → 23 Jul 2010

Publication series

Name	2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010

Conference

Conference	2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010
Country/Territory	Spain
City	Barcelona
Period	18/07/10 → 23/07/10

Access to Document

10.1109/CEC.2010.5586052

Cite this

Uy, N. Q., McKay, B., O'Neill, M., & Hoai, N. X. (2010). Self-adapting semantic sensitivities for Semantic Similarity based Crossover. In 2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010 Article 5586052 (2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010). https://doi.org/10.1109/CEC.2010.5586052

Uy, Nguyen Quang ; McKay, Bob ; O'Neill, Michael et al. / Self-adapting semantic sensitivities for Semantic Similarity based Crossover. 2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010. 2010. (2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010).

@inproceedings{b3f769352d21408983f84c4877a5a833,

title = "Self-adapting semantic sensitivities for Semantic Similarity based Crossover",

abstract = "This paper presents two methods for self-adapting the semantic sensitivities in a recently proposed semantics-based crossover: Semantic Similarity based Crossover (SSC) [1]. The first self-adaptation method is inspired by a self-adaptive method for controlling mutation step size in Evolutionary Strategies (1/5 rule). The design of the second takes into account more of our previous experimental observations, that SSC works well only when a certain portion of events successfully exchange semantically similar subtrees. These two proposed methods are then tested on a number of real-valued symbolic regression problems, their performance being compared with SSC using predetermined sensitivities and with standard crossover. The results confirm the benefits of the second self-adaption method.",

author = "Uy, {Nguyen Quang} and Bob McKay and Michael O'Neill and Hoai, {Nguyen Xuan}",

year = "2010",

doi = "10.1109/CEC.2010.5586052",

language = "English",

isbn = "9781424469109",

series = "2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010",

booktitle = "2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010",

note = "2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010 ; Conference date: 18-07-2010 Through 23-07-2010",

}

Uy, NQ, McKay, B, O'Neill, M & Hoai, NX 2010, Self-adapting semantic sensitivities for Semantic Similarity based Crossover. in 2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010., 5586052, 2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010, 2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010, Barcelona, Spain, 18/07/10. https://doi.org/10.1109/CEC.2010.5586052

Self-adapting semantic sensitivities for Semantic Similarity based Crossover. / Uy, Nguyen Quang; McKay, Bob; O'Neill, Michael et al.
2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010. 2010. 5586052 (2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - This paper presents two methods for self-adapting the semantic sensitivities in a recently proposed semantics-based crossover: Semantic Similarity based Crossover (SSC) [1]. The first self-adaptation method is inspired by a self-adaptive method for controlling mutation step size in Evolutionary Strategies (1/5 rule). The design of the second takes into account more of our previous experimental observations, that SSC works well only when a certain portion of events successfully exchange semantically similar subtrees. These two proposed methods are then tested on a number of real-valued symbolic regression problems, their performance being compared with SSC using predetermined sensitivities and with standard crossover. The results confirm the benefits of the second self-adaption method.

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T3 - 2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010

BT - 2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010

T2 - 2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010

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Uy NQ, McKay B, O'Neill M, Hoai NX. Self-adapting semantic sensitivities for Semantic Similarity based Crossover. In 2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010. 2010. 5586052. (2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010). doi: 10.1109/CEC.2010.5586052

Self-adapting semantic sensitivities for Semantic Similarity based Crossover

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