Some recent papers on evolutionary computation
Xin Yao
Dear All,
The following evolutionary computation papers are now available either
electronically or in hardcopies upon request. Comments and criticisms are
most welcome. Please send them to me by email.
Formally published proceedings have to be ordered from the publishers.
Best regards,
Xin
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| Dr Xin Yao |
| Senior Lecturer |
| Computational Intelligence Group Email: x...@csadfa.cs.adfa.oz.au |
| Department of Computer Science Tel: +61 6 268-8819 |
| University College Fax: +61 6 268-8581 |
| The University of New South Wales WWW: http://www.cs.adfa.oz.au/~xin |
| Australian Defence Force Academy |
| Canberra, ACT, Australia 2600 |
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Papers on Evolutionary Artificial Neural Networks
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1. X. Yao (1995g), "Evolutionary artificial neural networks," Invited
article. In {\em Encyclopedia of Computer Science and Technology}, Vol.33, ed.
A.~Kent and J. G. Williams, Marcel Dekker Inc., New York. pp.137-170. Also
appearing in {\em Encyclopedia of Library and Information Science}.
2. X. Yao and Y. Liu (1995), "Evolving artificial neural networks for
medical applications," In {\em Proc. of the First Korea-Australia Joint
Workshop on Evolutionary Computation}, pp.1-16, Taejon, Korea.
3. X. Yao and Y. Shi (1995), "A Preliminary Study on Designing
Artificial Neural Networks Using Co-Evolution," Invited paper, {\em Proc. of
IEEE Singapore International Conference on Intelligent Control and
Instrumentation (SICICI'95)}, pp.149--154, IEEE Singapore Section.
4. Y. Liu and X. Yao (1996a), "A population-based learning algorithm which
learns both architectures and weights of neural networks, " To appear in
{\em Chinese Journal of Advanced Software Research} (Allerton Press, Inc., New
York, NY 10011), Vol.~3, No.~1.
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Papers on Speciated Co-evolutionary Learning & Iterated Prisoner's Dilemma
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5. X. Yao and P. Darwen (1995), "An experimental study of N-person
iterated prisoner's dilemma games," In {\em Progress in Evolutionary
Computation}, (ed.) X. Yao, Lecture Notes in Artificial Intelligence, Vol.~956,
Springer-Verlag, Heidelberg, Germany, pp.90-108.
6. P. Darwen and X. Yao (1995b), "On evolving robust strategies for
iterated prisoner's dilemma," In {\em Progress in Evolutionary Computation},
(ed.) X. Yao, Lecture Notes in Artificial Intelligence, Vol.~956,
Springer-Verlag, Heidelberg, Germany, pp.276--292.
7. X. Yao (1995c), "Evolutionary stability in the {N}-person prisoner's
dilemma," Accepted by {\em BioSystems}.
8. P. Darwen and X. Yao (1995c), ``How good is fitness sharing with a scaling
function,'' Tech Rep CS8/95, Department of Computer Science, University
College, UNSW, Australian Defence Force Academy, Canberra, ACT, Australia 2600.
(Longer version of 9)
9. P. Darwen and X. Yao (1995a), "A dilemma for fitness sharing with a
scaling function," Accepted, {\em Proc. of 1995 IEEE Conference on
Evolutionary Computation (ICEC'95)}, Perth, Australia, IEEE Press.
10. P. Darwen and X. Yao (1996a), ``Automatic Modularisation by Speciation,''
Available in a few weeks.
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Papers on Genetic Grammatical Learning and Genetic Programming
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11. P. Whigham, "Inductive bias and genetic programming," Proc of the First
IEE/IEEE International Conf on Genetic Algorithms in Engineering Systems:
Innovations and Applications, Sheffield, UK, pp.461-466. 1995.
12. P. Whigham and R. McKay, "Genetic approaches to learning recursive
relations," In {\em Progress in Evolutionary Computation},
(ed.) X. Yao, Lecture Notes in Artificial Intelligence, Vol.~956,
Springer-Verlag, Heidelberg, Germany, pp.17-27. 1995.
13. P. Whigham, "A schema theorem for context-free grammars," Accepted, {\em
Proc. of 1995 IEEE Conference on Evolutionary Computation (ICEC'95)}, Perth,
Australia, IEEE Press. 1995.
14. P. Whigham, "Genetic programming and spatial information," Proceedings of
the 7th Australian Joint Conference on Artificial Intelligence (AI'94), ed.
C.~Zhang, J. Debenham and D. Lukose, World Scientific Publ. Co., Singapore,
pp.124-131. 1994.
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Other papers on Evolutionary Computation
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15. X. Yao (1996b), "An overview of evolutionary computation," To appear in
{\em Chinese Journal of Advanced Software Research} (Allerton Press, Inc., New
York, NY 10011), Vol.~3, No.~1.
16. X. Yao and Y. Liu (1996b), ``Fast evolutionary programming,'' Submitted.
17. G. Lin, X. Yao, I. Macleod, L. Kang, and Y. Chen (1995), "Parallel
genetic algorithms on PVM," To appear in {\em Proc. of the International
Conference on Parallel Algorithms (ICPA'95)}, Wuhan, P. R. China,
Gordon and Breach.
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Books and Journal Special Issue
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18. X. Yao (ed.) (1995g), {\em Proceedings of the Eighth Australian Joint
Conference on Artificial Intelligence (AI'95)}, World Scientific Publ. Co.,
Singapore, ISBN 981-02-2484-2.
Which contains the following papers on Evolutionary Computation:
K. A. De Jong, ``Evolving intelligence,'' pp.23-32. (Keynote speaker)
S. Ronald, J. Asenstorfer, and M. Vincent, ``Genetic algorithm test functions:
design a multimodal landscape in the permutation domain,'' pp.331-338.
M. A. Rosenman, ``An evolutionary model for non-routine design,'' pp.363-370.
T. Schnier and J. Gero, ``Learning representations for evolutionary
computation,'' pp.387-394.
J. Neves and M. Santos, ``A distributed computational environment for
genetic-based classifier systems,'' pp.467-474.
K.-C. Kim and J.-H. Kim, ``Evolutionary programming based
multicriteria fuzzy expert system,'' pp.475-482.
M. Salami and G. Cain, ``Implementation of genetic algorithms on
reprogrammable architectures,'' pp.581.
H. Myung and J.-H. Kim, ``Solving heavily constrained problems using
hybrid evolutionary optimization,'' pp.587.
19. X.Yao (ed.) (1995b), Progress in Evolutionary Computation, {\em Lecture
Notes in Artificial Intelligence, Volume 956}, Springer-Verlag, Heidelberg,
Germany, 1995 (ISBN 3-540-60154-6).
Table of Contents:
\begin{description}
\item[ ] The effect of function noise on GP efficiency
\newline {\em J. Y. B. Lee and P. C. Wong} \dotfill 1
\item[ ] Genetic approaches to learning recursive relations
\newline {\em P. A. Whigham and R. I. McKay} \dotfill 17
\item[ ] An application of genetic programming to the 4-OP problem using
\newline map-trees
\newline {\em T. Aytekin and E. E. Korkmaz and H. A. G{\"{u}}vennir} \dotfill 28
\item[ ] Direct replacement: a genetic algorithm without mutation which avoids
\newline deception
\newline {\em J. Rowe and I. East} \dotfill 41
\item[ ] Competitive evolution: a natural approach to operator selection
\newline {\em Q. Tuan Pham} \dotfill 49
\item[ ] Emergent collective computational abilities in interacting particle
systems
\newline {\em Z. Zhang, S. Bai and G.-J. Li} \dotfill 61
\item[ ] A perspective on evolutionary computation
\newline {\em Z. Michalewicz} \dotfill 73
\item[ ] An experimental study of N-person iterated prisoner's dilemma games
\newline {\em X. Yao and P. Darwen} \dotfill 90
\item[ ] A systolic architecture for high speed hypergraph partitioning using
\newline genetic algorithms
\newline {\em H. Chan and P. Mazumder} \dotfill 109
\item[ ] Development of hybrid optimisation techniques based on genetic
\newline algorithms and simulated annealing
\newline {\em K. P. Wong and S. Y. W. Wong} \dotfill 127
\item[ ] Development of parallel hybrid optimisation techniques based on
genetic
\newline algorithms and simulated annealing
\newline {\em K. P. Wong and S. Y. W. Wong} \dotfill 155
\item[ ] Genetic algorithms for cutting stock problems: with and without
\newline contiguity
\newline {\em R. Hinterding and L. Khan} \dotfill 166
\item[ ] GASBOR: A genetic algorithm for switchbox routing in integrated
circuits
\newline {\em J. Lienig and K. Thulasiraman} \dotfill 187
\item[ ] The calculus of self-modifiable algorithm based evolutionary computer
network routing
\newline {\em D. Seunarine and E. Eberbach} \dotfill 201
\item[ ] Evolving robot strategy for open ended game
\newline {\em T. Sugiyama, T. Kido and M. Nakanishi} \dotfill 225
\item[ ] An evolutionary approach to adaptive model-building
\newline {\em Z. Pan, L. Kang, J. He and Y. Liu} \dotfill 236
\item[ ] Training neural networks with influence diagrams
\newline {\em A. M. C. Machado and M. F. M. Campos} \dotfill 245
\item[ ] A behavioural theory of intelligent machines as a framework for the
\newline analysis of adaptation
\newline {\em C. A. Lindley} \dotfill 257
\item[ ] On evolving robust strategies for iterated prisoner's dilemma
\newline {\em P. J. Darwen and X. Yao} \dotfill 276
\item[ ] Comparison of heuristic search algorithms for single machine
\newline scheduling problems
\newline {\em G. McMahon and D. Hadinoto} \dotfill 293
\item[ ] Encoding graphs for genetic algorithms: an investigation using the
\newline minimum spanning tree problem
\newline {\em P. Piggott and F. Suraweera} \dotfill 305
20. Journal special issue {\em Informatica: An International
Journal of Computing and Informatics, Volume~18, No.~4, December 1994}.
\begin{description}
\item[ ] D. T. Crosher, ``The artificial evolution of adaptive processes,''
pp.377--386.
\item[ ] L. J. Fogel, D. B. Fogel and P. J. Angeline, ``A preliminary
investigation on extending evolutionary programming to include self-adaptation
on finite state machines,'' pp.387--398.
\item[ ] T.Kido, K. Takagi and M. Nakanishi, ``Analysis and comparisons of
genetic algorithm, simulated annealing, tabu search and evolutionary
combination algorithm,'' pp.399--410.
\item[ ] M. Tomita and T. Kido, ``Sacrificial acts in single round prisoner's
dilemma,'' pp.411--416.
\item[ ] J. Vaario, ``From evolutionary computation to computational
evolution,'' pp.417--434.
\item[ ] X. Yao and P. J. Darwen, ``An experimental study of N-person iterated
prisoner's dilemma games,'' pp.435--450.
\end{description}
21. Proc. of the First Korea-Australia Joint Workshop on Evolutionary
Computation, Sept. 1995, Taejon, Korea.
(Limited copies are available. Ask Prof Kim at joh...@vivaldi.kaist.ac.kr for
more details.)