Abstract
Population measures for genetic programs are defined and analysed in an attempt to better understand the behaviour of genetic programming. Some measures are simple, but do not provide sufficient insight. The more meaningful ones are complex and take extra computation time. Here we present a unified view on the computation of population measures through an information hyper-tree (iTree). The iTree allows for a unified and efficient calculation of population measures via a basic tree traversal.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Burke, E., Gustafson, S., Kendall, G., Krasnogor, N.: Advanced population diversity measures in genetic programming. In: Guervós, J.J.M., Adamidis, P.A., Beyer, H.-G., Fernández-Villacañas, J.-L., Schwefel, H.-P. (eds.) PPSN 2002. LNCS, vol. 2439, pp. 341–350. Springer, Heidelberg (2002)
Colless, D.H.: Review of phylogenetics: The theory and practice of phylogenetic systematics. Syst. Zool. 31, 100–104 (1982)
Daida, J., Hilss, A., Ward, D., Long, S.: Visualizing tree structures in genetic programming. In: Cantú-Paz, E., Foster, J.A., Deb, K., Davis, L., Roy, R., O’Reilly, U.-M., Beyer, H.-G., Kendall, G., Wilson, S.W., Harman, M., Wegener, J., Dasgupta, D., Potter, M.A., Schultz, A., Dowsland, K.A., Jonoska, N., Miller, J., Standish, R.K. (eds.) GECCO 2003. LNCS, vol. 2724, pp. 1652–1664. Springer, Heidelberg (2003)
Daida, J., Li, H., Tang, R., Hilss, A.: What makes a problem GP-hard? validating a hypothesis of structural causes. In: Cantú-Paz, E., Foster, J.A., Deb, K., Davis, L., Roy, R., O’Reilly, U.-M., Beyer, H.-G., Kendall, G., Wilson, S.W., Harman, M., Wegener, J., Dasgupta, D., Potter, M.A., Schultz, A., Dowsland, K.A., Jonoska, N., Miller, J., Standish, R.K. (eds.) GECCO 2003. LNCS, vol. 2724, pp. 1665–1677. Springer, Heidelberg (2003)
Ekárt, A., Németh, S.: Maintaining the diversity of genetic programs. In: Foster, J.A., Lutton, E., Miller, J., Ryan, C., Tettamanzi, A.G.B. (eds.) EuroGP 2002. LNCS, vol. 2278, pp. 162–171. Springer, Heidelberg (2002)
Keijzer, M.: Efficiently representing populations in genetic programming. In: Angeline, P.J., Kinnear Jr., K.E. (eds.) Advances in Genetic Programming 2, ch. 13, pp. 259–278. MIT Press, Cambridge (1996)
Lu, S.-Y.: The tree-to-tree distance and its application to cluster analysis. IEEE Transactions on PAMI 1(2), 219–224 (1979)
O’Reilly, U.-M.: Using a distance metric on genetic programs to understand genetic operators. In: Koza, J.R. (ed.) Late Breaking Papers at the 1997 Genetic Programming Conference, pp. 199–206 (1997)
Selkow, S.M.: The tree-to-tree editing problem. Information Processing Letters 6(6), 184–186 (1977)
Wineberg, M., Oppacher, F.: Distance between populations. In: Cantú-Paz, E., Foster, J.A., Deb, K., Davis, L., Roy, R., O’Reilly, U.-M., Beyer, H.-G., Kendall, G., Wilson, S.W., Harman, M., Wegener, J., Dasgupta, D., Potter, M.A., Schultz, A., Dowsland, K.A., Jonoska, N., Miller, J., Standish, R.K. (eds.) GECCO 2003. LNCS, vol. 2724, pp. 1481–1492. Springer, Heidelberg (2003)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2004 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Ekárt, A., Gustafson, S. (2004). A Data Structure for Improved GP Analysis via Efficient Computation and Visualisation of Population Measures. In: Keijzer, M., O’Reilly, UM., Lucas, S., Costa, E., Soule, T. (eds) Genetic Programming. EuroGP 2004. Lecture Notes in Computer Science, vol 3003. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24650-3_4
Download citation
DOI: https://doi.org/10.1007/978-3-540-24650-3_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-21346-8
Online ISBN: 978-3-540-24650-3
eBook Packages: Springer Book Archive