Abstract
Metalevel architectures are gaining widespread use in many domains. This paper examines the metalevel as a system level, describes the type of knowledge embodied in a metalevel, and discusses the characteristics of good metalevel representations.
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
Bell C., Adey S., T. Urwin, Jones G., Simpson R. and Sadri F., Report of the Short Session on Planning and Control, Report of Fourth Planning SIG Workshop. Alvey Programme IKBS Research Theme, Alvey Directorate, London, England, 1985.
Benjamin D. P., Using a Metatheory as a Functional Representation, International journal of Intelligent Systems, volume 3 (3), Fall 1988.
Benjamin D. P., A Metatheory for Reasoning about Preconditions, TR-87–055, Philips Laboratories, 1987.
Benjamin D. P., Learning Strategies by Reasoning about Rules, 10th International Joint Conference on Artificial Intelligence; Milano, Italy, August 1987.
Bosman A., Decision Support Systems, Corporate Models and the Handling of Organisations, INFORMATIE23,11 (1981), pp. 681–92.
Bundy A. and Welham B., Using Meta-Level Inference for Selective Application of Multiple Rewrite Rule Sets in Algebraic Manipulation, Artificial Intelligence 16 (1981), pp. 189–212.
Bundy A., Meta-level Inference and Consciousness, in The Mind and the Machine, S. Torrance (editor), Horwood, 1984.
Dietterich T., Learning at the Knowledge Level, Machine Learning 1 (1986), pp. 287–316.
Kedar-Cabelli S. and McCarty L. T., Explanation-Based Generalization as Resolution TfaeoremProving,Proc.4thInternationalWorkshoponMachineLearning,Morgm Kaufmann, Los Altos, CA, 1987, pp. 383–389.
Levesque H., A Functional Approach to Knowledge Representation, Artificial Intelligence 23 (1984), pp. 155–212.
Lowry M. R., Algorithm Synthesis Through Problem Reformulation, Ph. D. Dissertation, Stanford University, 1987.
McClintock C. G., The Metatheorectical Bases of Social Psychological Theory, Behav. Sci. 30,3 (1985), pp. 155–73.
Michalski R. S., A Theory and Methodology of Inductive Learning, Artificial Intelligence 20 (February 1983), pp. 111–161.
Morris E. K., Higgins S. T. and Bickel W. K., Comments on cognitive science in the experimental analysis of behavior, Behavior Analyst 5 (2) (1982), pp. 109–125.
Newell A., The Knowledge Level, Artificial Intelligence 18,2 (1982), pp. 87–127.
Perrault C. R., On the Mathematical Properties of Linguistic Theories, Comput. Linguist. 10, 3–4 (1984), pp. 165–76.
Pylyshyn Z. W., Computation and Cognition, MIT Press, Cambridge, MA, 1984.
Silver B., Metalevel Inference, Elsevier Science, Amsterdam, Netherlands, 1986.
Stanoulov N., An Evolutionary Approach in Information Systems Science, J. Am. Soc. Inf. Sci. 33, 5 (1982), pp. 311–16.
Teske J. A. and Pea R. D., Metatheoretical Issues in Cognitive Science., Journal of Mind & Behavior 2 (2) (1981), pp. 123–178.
Thompson T. F. and Wojcik R. M.,MELD: An Implementation of aMeta-Level Architecture forPwcessDiagnosis,ProceedingsoftheFirstConferenceonArtificialIntelligence Applications, December 1984, pp. 321–330.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1990 Kluwer Academic Publishers
About this chapter
Cite this chapter
Benjamin, D.P. (1990). A Metalevel Manifesto. In: Brazdil, P.B., Konolige, K. (eds) Machine Learning, Meta-Reasoning and Logics. The Kluwer International Series in Engineering and Computer Science, vol 82. Springer, Boston, MA. https://doi.org/10.1007/978-1-4613-1641-1_1
Download citation
DOI: https://doi.org/10.1007/978-1-4613-1641-1_1
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4612-8906-7
Online ISBN: 978-1-4613-1641-1
eBook Packages: Springer Book Archive