INDIN’03 Workshop Technical Program

Keynote

Automatic Divide-and-Conquer Using Populations and Ensembles

Xin Yao*, University of Birmingham, UK

Abstract

Many real-world problems are too large and complex for a single monolithic system to solve. The divide-and-conquer strategy has often been used in practice to break a large problem into tractable smaller sub-problems and then solve them. However, useful division of a large and complex problem often requires experienced human experts and rich prior domain knowledge, which are usually unavailable for real-world problems. This talk describes some of our research efforts towards an automatic approach to divide-and-conquer. By evolving and training a team of specialists from random initial conditions, we were able to "decompose" a large and complex problem into simpler ones and solve them without human intervention. Two major approaches will be described. One uses the population structure in evolutionary algorithms, where individuals in a population are evolved into species (i.e., specialists for solving sub-problems). The other uses neural network ensembles in which individual neural networks learn to differentiate from and cooperate with each other. A constructive algorithm for designing ensembles as well as individual neural networks will be introduced.

Biosketch of the speaker:

 

Dr. Xin Yao is a professor of computer science at the University of Birmingham, UK. He is a fellow of IEEE, the chair of the IEEE NNS Technical Committee on Evolutionary Computation and the Editor-in-Chief of IEEE Transactions on Evolutionary Computation. He is also an associate editor or an editorial board member of several other international journals. He has chaired or co-chaired 16 international conferences in evolutionary computation in recent years, and has been invited to present a keynote or plenary talk at many international conferences. He held a visiting professorship at several universities in China and Australia. He was the recipient of the 2001 IEEE Donald G. Fink Prize Paper Award. His major research interests include evolutionary computation (especially learning and optimization), neural network ensembles, evolvable hardware, data mining, and computational time complexity of evolutionary algorithms.


*Professor Xin Yao

The Centre of Excellence for Research in Computational Intelligence and Applications (CERCIA)      URL: http://www.cercia.ac.uk

School of Computer Science

The University of Birmingham

Edgbaston, Birmingham B15 2TT

United Kingdom

Phone: +44 121 414 3747

Fax:  +44 121 414 4281

Email: x.yao@cs.bham.ac.uk

URL: http://www.cs.bham.ac.uk/~xin