Output details
11 - Computer Science and Informatics
Bangor University
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Output 0 of 0 in the submission
Output title
Constituent Grammatical Evolution
Type
E - Conference contribution
Name of conference/published proceedings
Proceedings of the International Joint Conference on Artificial Intelligence
Volume number
2011
Issue number
-
First page of article
1261
ISSN of proceedings
-
Year of publication
2011
URL
-
Number of additional authors
1
Additional information
<22>This paper was presented at the IJCAI conference, one of the two top-ranked AI conferences (acceptance rate for oral paper was 17%, 227/1325). The work describes a new evolutionary algorithm (CGE) based on Grammatical Evolution which introduces constituent genes and conditional behaviour switching. The experimental results show that CGE is able to find state-of-the-art solutions for benchmarking problems such as the Santa Fe and Los Altos Hills trails. The results also show that CGE significantly outperforms GE in terms of both efficiency (percent of solutions found) and effectiveness (number of required steps of solutions found) on all the benchmarking problems.
Interdisciplinary
-
Cross-referral requested
-
Research group
None
Citation count
1
Proposed double-weighted
No
Double-weighted statement
-
Reserve for a double-weighted output
No
Non-English
No
English abstract
-
