Up: Visualisation of Hierarchical Cost Previous: Discussion and Conclusions

Bibliography

1

D.H. Wolpert and W.G. Macready.
No free lunch theorems for optimization.
IEEE Transactions on Evolutionary Computation, 1(1):67-82, 1997.

2

S.Christensen and F.Oppacher.
What can we learn from No Free Lunch? A first attempt to characterize the concept of a searchable function.
In Proceedings of the Genetic and Evolutionary Computation Conference, pages 1219-1226, San Francisco, CA, 2001. Morgan Kaufmann.

3

T.C. Belding.
Potholes on the royal road.
In Proceedings of the Genetic and Evolutionary Computation Conference, pages 211-218, San Francisco, CA, 2001. Morgan Kaufmann.

4

S.Kauffman.
The Origins of Order.
Oxford University Press, NY, 1993.

5

E.R. Tufte.
The Visual Display of Quantitative Information.
Graphic Press, reprint edition edition, 1992.

6

J.H. Friedman and J.W. Tukey.
A projection pursuit algorithm for exploratory data analysis.
IEEE Transactions on Computers, 23(9):881-889, September 1974.

7

A.N. Pryke.
The Haiku Visualisation System.
PhD thesis, University of Birmingham, 1996.

8

A.Buja and D.Asimov.
Grand tour methods: An outline.
In Proceedings of the 18th Symposium on the Interface, pages 63-67. American Statistical Association, 1986.

9

J.H. Holland.
Adaptation in Natural and Artificial Systems.
University of Michigan Press, Ann Arbor, 1975.

10

J.H. Holland.
Building blocks, cohort genetic algorithms, and hyperplane-defined functions.
Evolutionary Computation, 8(4):373-391, 2000.

11

S.Forrest and M.Mitchell.
What makes a problem hard for a genetic algorithm? Some anomalous results and their explanation.
Machine Learning, 13(2/3):285-319, 1993.

12

M.Mitchell, J.H. Holland, and S.Forrest.
When will a genetic algorithm outperform hill climbing.
In Advances in Neural Information Processing Systems, volume6, pages 51-58, 1994.

13

M.Mitchell.
An introduction to genetic algorithms.
MIT Press, Cambridge, MA, 1996.

14

D.E. Goldberg, K.Deb, and B.Korb.
Messy genetic algorithms: Motivation, analysis and first results.
Complex Systems, 3:493-530, 1989.

15

R.A. Watson and J.B. Pollack.
Hierarchically-consistent test problems for genetic algorithms.
In P.J. Angeline, Z.Michalewicz, M.Schoenauer, X.Yao, and A.Zalzala, editors, Proceedings of 1999 Congress on Evolutionary Computation, pages 1406-1413. IEEE Press, 1999.

16

R.A. Watson, G.S. Hornby, and J.B. Pollack.
Modeling building-block interdependency.
Parallel Problem Solving from Nature, proceedings of the Fifth International Conference, pages 97-106, 1998.

17

M.Pelikan and D.E. Goldberg.
Hierarchical problem solving by the bayesian optimization algorithm.
IlliGAL Report No. 2000002, Illinois Genetic Algorithms Laboratory, University of Illinois at Urbana-Champaign, Urbana, IL, 2000.

---