Machine Learning

, Volume 3, Issue 1, pp 5–8 | Cite as

Machine Learning as an Experimental Science

  • Pat LangleyEmail author
Editorial Introduction


  1. Fisher, D.H.(1987).Knowledge acquisition via incremental conceptual clustering.Machine Learning,2,139–172.Google Scholar
  2. Lebowitz, M.(1987).Experiments with incremental concept formation:UNI-MEM.Machine Learning,2,103–138.Google Scholar
  3. Minton, S.N.(1985).Selectively generalizing plans for problem solving.Proceedings of the Ninth International Joint Conference on Artificial Intelligence(pp.596–599).Los Angeles,CA: Morgan Kaufmann.Google Scholar
  4. Schlimmer, J.C.(1987).Incremental adjustment of representations for learning.Proceedings of the Fourth International Workshop on Machine Learning(pp.79–90).Irvine,CA: Morgan KaufmannGoogle Scholar
  5. Schlimmer, J.C., & Fisher, D.H.(1986).A case study of incremental concept induction.Proceedings of the Fifth National Conference on Artificial Intelligence(pp.496–501).Philadelphia,PA: Morgan Kaufmann.Google Scholar
  6. Simon, H.A.(1969).The sciences of the artificial.Cambridge,MA: MIT Press.Google Scholar
  7. Stepp, R.E.(1984),Conjunctive conceptual clustering:A methodology and experimentation.Doctoral dissertation,Department of Computer Science, University of Illinois, Urbana.Google Scholar
  8. Quinlan, J.R.(1986).Induction of decision trees.Machine Learning,1,81–106.Google Scholar

Copyright information

© Kluwer Academic Publishers 1988

Authors and Affiliations

  1. 1.Irvine.

Personalised recommendations