Abstract
To solve the Imperfect Theory Problem (ITP) faced by Explanation Based Generalization (EBG), this paper proposes a methodology, Deep Knowledge Based Learning Methodology (DKBLM) by name, and gives an implementation of DKBLM, called Hierarchically Distributed Learning System (HDLS). As an example of HDLS's application, this paper shows a learning system (MLS) in meteorology domain and its running with a simplified example.
DKBLM can acquire experiential knowledge with causality in it. It is applicable to those kinds of domains, in which experiments are relatively difficult to carry out, and in which there exist many available knowledge systems at different levels for the same domain (such as weather forecasting).
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
G. DeJong and R.Mooney, Explanation-based learning: an alternative view. Tech. Rep. UILU-ENG-86-2208, 1986.
S.Rajamoney, G.DeJong and B.Faltings, Towards a model of conceptual knowledge acquisition through directed experimentation. IJCAI-85, 1985, pp.688–690.
S.Rajamoney, The classification, detection and handling of imperfect theory problems. IJCAI-87, 1987, pp.205–207.
B.Silver, Learning equation solving methods from examples. IJCAI-83, 1983, pp. 429–431.
S.Salzberg, Heuristics for inductive learning. IJCAI-85, 1985, pp.603–609.
P.Winston, Artificial Intelligence. Addison-Wesley, 1977.
J.Carbonell, Experimental learning in analogical problem solving. AAAI-82, 1982, pp. 168–171.
J.Carbonell, Learning by analogy, formulating and generalizing plans from past experience. InMachine Learning, Ed. by R.Michalski, J.Carbonell and T.Mitchell Vol. 1, Springer-Verlag, 1984.
Z.Ma and W.Zou, On the levels of knowledge and deep knowledge. Proc. of Int'l. Conf. for Young Computer Scientists, 1991, Beijing, pp.442–445.
R.Michalski, J.Carbonell and T.Mitchell (Ed.), Machine Learning, Vol.1. Springer-Verlag, 1984.
Z.ma, R.Zhao and F.Su, A representation for time and inference on persistence with uncertainty in weather forecast. Proc. of Int'l. Conf. on Next Generation Computing Systems, 1989, Beijing, pp.22–26.
Author information
Authors and Affiliations
Rights and permissions
About this article
Cite this article
Ma, Z. DKBLM — Deep knowledge based learning methodology. J. of Compt. Sci. & Technol. 8, 379–384 (1993). https://doi.org/10.1007/BF02939547
Received:
Revised:
Issue Date:
DOI: https://doi.org/10.1007/BF02939547