Xin Yao's Research Interests: Co-evolution
The most prominent characteristic of co-evolution is that the fitness of an
individual depends on fitness of other individuals, which can be from the same
population or a different population. Co-evolution can be used in both learning
and optimisation although my own research has mainly been in learning. I am
particularly interested in (1) the generalisation issue in co-evolutionary
learning, (2) how to encourage "arms race" in co-evolution, (3)
interactions/combinations between co-evolution and fitness sharing for automatic
modularisation, and (4) how fitness landscapes (for different individuals)
change and interact dynamically in co-evolution.
I have used the iterated prisoner's dilemma as an example in the study of
co-evolutionary learning although neural networks were also used. I am
collaborating with Dr Paul Darwen (Australia), Dr Sung-Bae Cho and Mr Yeon-Gyu
Seo (South Korea) in this area. Part of my work was supported by the Australian
- P. Darwen and X. Yao, ``Co-Evolution in Iterated Prisoner's Dilemma
with Intermediate Levels of Cooperation: Application to Missile Defense,''
International Journal of Computational Intelligence and Applications,
Available from World Scientific's web site as
a PDF file.
- P. J. Darwen and X. Yao, ``Why More Choices Cause Less Cooperation in
Iterated Prisoner's Dilemma,'' Proceedings of the 2001 Congress on
Evolutionary Computation, pp.987-994,
IEEE Press, Piscataway, NJ, USA, May 2001.
a PDF file.
- Y.-G. Seo, S.-B. Cho and X. Yao, ``The Impact of Payoff Function and
Local Interaction on the N-player Iterated Prisoner's Dilemma,''
Knowledge and Information Systems: An International Journal.
2(4):461-478, November 2000.
- P. J. Darwen and X. Yao, ``Does extra genetic diversity maintain
escalation in a co-evolutionary arms race,'' International
Journal of Knowledge-Based Intelligent Engineering Systems,
4(3):191-200, July 2000.
- Y.-G. Seo, S.-B. Cho and X. Yao, ``Exploiting Cooperative Coalition in
Co-Evolutionary Learning,'' Proceedings of the 2000 Congress on
Evolutionary Computation, IEEE Press, Piscataway, NJ, USA, July 2000.
- X. Yao and P. J. Darwen, ``How Important Is Your Reputation in a
Multi-Agent Environment,'' Proc. of the 1999 IEEE Conference on Systems,
Man, and Cybernetics, IEEE Press, Piscataway, NJ, USA, pp.II-575 - II-580,
- Y.-G. Seo, S.-B. Cho and X. Yao, ``Emergence of Cooperative Coalition in
NIPD game with Localization of Interaction and Learning,'' Proc. of the
1999 Congress on Evolutionary Computation, Vol. 2, IEEE Press, Piscataway,
NJ, USA, pp.877-884, July 1999.
- P. J. Darwen and X. Yao, ``Speciation as automatic categorical
modularization,'' IEEE Transactions on Evolutionary
Computation, 1(2):101-108, 1997.
- X. Yao, ``Automatic acquisition of strategies by co-evolutionary
learning,'' Proc. of the International Conference on Computational
Intelligence and Multimedia Applications (ICCIMA'97), Gold Coast,
Australia, 10-12 February 1997, pp.23-29.
- X. Yao, Y. Liu and P. Darwen,
``How to make
best use of evolutionary learning,'' Complexity International:
An Electronic Journal of Complex Systems Research (ISSN 1320-0682),
Vol. 3, July 1996.
Also appeared in paper form in Complex Systems --- From Local
Interactions to Global Phenomena, IOS Press, Amsterdam, pp.229--242, 1996.
- P. Darwen and X. Yao (1996a), ``Automatic modularisation by speciation,''
Proc. of the Third IEEE International Conference on
Evolutionary Computation (ICEC'96), Nagoya, Japan, 20-22 May 1996,
- P. Darwen and X. Yao (1996b), ``Every niching method has its niche:
fitness sharing and implicit sharing compared,'' Proc. of Parallel Problem
Solving from Nature (PPSN) IV, Vol.1141, Lecture Notes in Computer
Science, Springer-Verlag, Berlin, pp.398-407, 1996.
- P. Darwen and X. Yao (1995a), ``A dilemma for fitness sharing with a
scaling function,'' Proc. of 1995 IEEE Conference on Evolutionary
Computation (ICEC'95), Perth, Australia, IEEE Press, pp.166-171.
- P. Darwen and X. Yao (1995b), ``On evolving robust strategies for
iterated prisoner's dilemma,'' In Progress in Evolutionary
Computation, Lecture Notes in Artificial Intelligence, Vol. 956,
Springer-Verlag, Heidelberg, Germany, pp.276-292.
- X. Yao and Y. Shi (1995), ``A Preliminary Study on Designing
Artificial Neural Networks Using Co-Evolution,'' Invited paper, Proc. of
IEEE Singapore International Conference on Intelligent Control and
Instrumentation (SICICI'95), pp.149-154, IEEE Singapore Section.
Last update: 5 September 2000