Page 227 - 49A Field Guide to Genetic Programming

BIBLIOGRAPHY 213

polytechnique.frzSzpaperszSzmarczSzAGP2.pdf/schoenauer96evolutionary.pdf.
GPBiB
M. Schoenauer, K. Deb, G. Rudolph, X. Yao, E. Lutton, J. J. Merelo, and H.-P. Schwefel,
editors. Parallel Problem Solving from Nature - PPSN VI 6th International Confer-
ence, volume 1917 of LNCS, Paris, France, 16-20 September 2000. Springer Verlag.
ISBN 3-540-41056-2. URL http://www.springer.de/cgi-bin/search_book.pl?isbn=
3-540-41056-2. GPBiB
D. P. Searson, G. A. Montague, and M. J. Willis. Evolutionary design of process con-
trollers. In In Proceedings of the 1998 United Kingdom Automatic Control Coun-
cil International Conference on Control (UKACC International Conference on Con-
trol ’98), volume 455 of IEE Conference Publications, University of Wales, Swansea,
UK, 1-4 September 1998. Institution of Electrical Engineers (IEE). URL http:
//www.staff.ncl.ac.uk/d.p.searson/docs/Searsoncontrol98.pdf. GPBiB
L. Sekanina. Evolvable Components: From Theory to Hardware Implementations. Natural
Computing. Springer-Verlag, 2003. ISBN 3-540-40377-9. URL http://www.fit.vutbr.
cz/~sekanina/ehw/books.html.en.
H.-S. Seok, K.-J. Lee, and B.-T. Zhang. An on-line learning method for object-
locating robots using genetic programming on evolvable hardware. In M. Sugisaka
and H. Tanaka, editors, Proceedings of the Fifth International Symposium on Artifi-
cial Life and Robotics, volume 1, pages 321–324, Oita, Japan, 26-28 January 2000. URL
http://bi.snu.ac.kr/Publications/Conferences/International/AROB00.ps. GPBiB
C. Setzkorn. On The Use Of Multi-Objective Evolutionary Algorithms For Classification
Rule Induction. PhD thesis, University of Liverpool, UK, March 2005. GPBiB
S. C. Shah and A. Kusiak. Data mining and genetic algorithm based gene/SNP selection.
Artificial Intelligence in Medicine, 31(3):183–196, July 2004. URL http://www.icaen.
uiowa.edu/~ankusiak/Journal-papers/Gen_Shital.pdf. GPBiB
Y. Shan, H. Abbass, R. I. McKay, and D. Essam. AntTAG: a further study. In R. Sarker
and B. McKay, editors, Proceedings of the Sixth Australia-Japan Joint Workshop on
Intelligent and Evolutionary Systems, Australian National University, Canberra, Aus-
tralia, 30 November 2002. GPBiB
Y. Shan, R. I. McKay, H. A. Abbass, and D. Essam. Program evolution with explicit
learning: a new framework for program automatic synthesis. In R. Sarker, et al.,
editors, Proceedings of the 2003 Congress on Evolutionary Computation CEC2003,
pages 1639–1646, Canberra, 8-12 December 2003. IEEE Press. ISBN 0-7803-7804-0.
URL http://citeseer.ist.psu.edu/560804.html. GPBiB
Y. Shan, R. I. McKay, R. Baxter, H. Abbass, D. Essam, and N. X. Hoai. Grammar
model-based program evolution. In Proceedings of the 2004 IEEE Congress on Evo-
lutionary Computation, pages 478–485, Portland, Oregon, 20-23 June 2004. IEEE
Press. ISBN 0-7803-8515-2. URL http://sc.snu.ac.kr/courses/2006/fall/pg/aai/
GP/shan/scfgcec04.pdf. GPBiB
Y. Shan, R. I. McKay, D. Essam, and H. A. Abbass. A survey of probabilistic model
building genetic programming. In M. Pelikan, et al., editors, Scalable Optimization
via Probabilistic Modeling: From Algorithms to Applications. Springer, 2006. ISBN
3-540-34953-7. GPBiB
S. Sharabi and M. Sipper. GP-sumo: Using genetic programming to evolve sumobots.
Genetic Programming and Evolvable Machines, 7(3):211–230, October 2006. ISSN
1389-2576. GPBiB
100 1000 2
Avg Size Avg Fitness sin(x)
Best Fitness GP (gen=50)
90
1.5
80
1
70
100
0.5
60
Generation 50 Average Size 50 Fitness 0
40 -0.5
10
30
(see Sec. B.4) 20 -1
-1.5
10
1 -2
0 20 40 60 80 100 0 20 40 60 80 100 0 1 2 3 4 5 6
Generations Generations x