- author = "Byoung-Tak Zhang and Dong-Yeon Cho",
- title = "Genetic Programming with Active Data Selection",
- booktitle = "Simulated Evolution and Learning: Second Asia-Pacific Conference on Simulated Evolution and Learning, SEAL'98. Selected Papers",
- year = "1998",
- editor = "R. I. Bob McKay and X. Yao and Charles S. Newton and J.-H. Kim and T. Furuhashi",
- volume = "1585",
- series = "LNAI",
- pages = "146--153",
- address = "Australian Defence Force Academy, Canberra, Australia",
- publisher_address = "Heidelberg",
- month = "24-27 " # nov,
- publisher = "Springer-Verlag",
- note = "published in 1999",
- keywords = "genetic algorithms, genetic programming",
- ISSN = "0302-9743",
-
URL = "
http://bi.snu.ac.kr/Publications/Journals/International/LNAI1585.pdf",
-
DOI = "
doi:10.1007/3-540-48873-1_20",
- size = "8 pages",
- abstract = "Genetic programming evolves Lisp-like programs rather than fixed size linear strings. This representational power combined with generality makes genetic programming an interesting tool for automatic programming and machine learning. One weakness is the enormous time required for evolving complex programs. In this paper we present a method for accelerating evolution speed of genetic programming by active selection of fitness cases during the run. In contrast to conventional genetic programming in which all the given training data are used repeatedly, the presented method evolves programs using only a subset of given data chosen incrementally at each generation. This method is applied to the evolution of collective behaviors for multiple robotic agents. Experimental evidence supports that evolving programs on an incrementally selected subset of fitness cases can significantly reduce the fitness evaluation time without sacrificing generalization accuracy of the evolved programs.",
-
notes = "SEAL'98 Published as springer-verlag LNAI 1585
SEAL98#058
A1 Artificial Intelligence Lab (SCAI) Dept. of Computer Engineering Seoul National University Seoul 151-742, Korea {btzhang, dycho}@scai.snu.ac.kr http://scai.snu.ac.kr/",
