Abstract
The objective of this paper is to discuss some general requirements for knowledge representation formalisms used in learning systems. Some general examples of learning tasks are examined, and it is discussed how the extent of these tasks determines the requirements which must be fulfilled by the knowledge representation used in the learning program. It is argued that learning tasks in which the output of one learning stage is "looped back" as input to the next brings about specific requirements for the knowledge representation and for the maintenance of knowledge. A logic-based system is described which fulfills these requirements, allows the representation of the epistemological states of a learning program, and offers mechanisms necessary to solve "real world" learning tasks. As a case study, the possible use of a multiple theory representation is described in more detail.
Preview
Unable to display preview. Download preview PDF.
7 References
Adams, D. (88): "Dirk Gently's Holistic Detective Agency"; Pan Books, London, 1988
Attardi, G./ Simi, M. (84): "Metalanguage and Reasoning about Viewpoints"; Proc. European Conference on Artificial Intelligence, 1984
Belnap, N.D. (76): "How a Computer Should Think"; In: G. Reyle (ed.): Contemporary Aspects of Philosophy, Oriente Press, 1976
Bentrup, J.A./ Mehler, G.J./ Riedesel, J.D. (87): "INDUCE 4: A Program for Incrementally Learning Structural Descriptions from Examples"; ISG Report 87-2, University of Illinois at Urbana-Champaign, 1987
Bowen, K.A. (85): "Meta-Level Programming and Knowledge Representation"; New Generation Computing, Vol. 3, 1985, pp. 359–383
Brazdil, P.B. (86a): "Transfer of Knowledge between Systems: Use of Meta-Knowledge in Debugging"; To appear in: Y. Kodratoff, A. Hutchinson (eds.): Machine and Human Learning, Horwood Pub.
Brazdil, P.B. (86b): "Transfer of Knowledge between Systems: A Common Approach to Teaching and Learning"; In Proc. ECAI-86, Brighton, 1986, pp. 73–78 (Volume II)
Brazdil, P.B. (87): "Knowledge States and Meta-Knowledge Maintenance"; In: I. Bratko, N. Lavrac (eds.): Progress in Machine Learning — Proceedings of the EWSL-87, Bled, Yugoslavia, Sigma Press, Wilmslow, 1987, pp. 138–146
Brebner, P.C. (85): "Paradigm Directed Computer Learning"; Master's Thesis, Computer Science Department, University of Waikato, Hamilton, New Zealand, 1985
Collins, A.M./ Quillian, M.R. (72): "Experiments on Semantic Memory and Language Comprehension"; In: L.W. Gregg (ed.): Cognition in Learning and Memory, 1972
Dietterich, T.G./ London, B./ Clarkson, K./ Dromey, G.(82): "Learning and Inductive Inference"; In: P.R. Cohen/E.A. Feigenbaum (eds.): The Handbook of Artificial Intelligence, Chapter XIV, Volume 3, Kaufmann, Los Altos, 1982, pp.325–605
Dietterich, T.G./ Michalski, R.S. (83): "Inductive Learning of Structural Descriptions: Evaluation Criteria and Comparative Review of Selected Methods"; In: R.S. Michalski/ J.G. Carbonell/ T.M. Mitchell (eds.): Machine Learning, Tioga, Palo Alto, 1983, pp. 41–81
Emde, W. (86): "Big Flood in the Blocks World (or Non-Cumulative Learning)"; In: B. Boulay, D. Hogg, L. Steels (eds.): Advances in Artificial Intelligence II (7th ECAI-86, Brighton, England, 1986), Elsevier Pub. (North Holland), Amsterdam, 1987, pp. 103–109
Emde, W. (87): "Non-Cumulative Learning in METAXA.3"; KIT-Report 56, Fachbereich Informatik, Technische Universität Berlin, 1987, a short version appeared in: Proc.IJCAI-87, Milan, Italy, 1987, pp. 208–210
Emde, W./ Habel, Ch./ Rollinger, C.-R. (83): "The Discovery of the Equator (or Concept Driven Learning)"; In: Proc. IJCAI-83, Karlsruhe, F.R.G, 1983, pp. 569–575
Emde, W./ Morik, K. (86): "Consultation Independent Learning"; To appear in: Y.Kodratoff/ A. Hutchinson (eds.): Human and Machine Learning, Horwood Pub.
Emde, W./ Rollinger, C.-R. (87): "Wissensrepräsentation und Maschinelles Lernen"; In: G. Rahmsdorf (ed.): Wissensrepräsentation in Expertensystemen, Springer, Berlin, 1988, pp. 172–189
Emde, W./ Schmiedel, A. (83): "Aspekte der Verarbeitung unsicheren Wissens"; KIT-Report 6, Fachbereich Informatik, Technische Universität Berlin, 1983
Fisher, D.H. (87): "Knowledge Acquisition Via Incremental Conceptual Clustering"; In: Machine Learning 2(2), 1987, pp. 139–172
Flann, N.S./ Dietterich, T.G. (86): "Selecting Appropriate Representations for Learning from Examples"; In: Proc. AAAI-86, Phil., PA, 1986, pp. 460–466
Haase, K.W. (86): "Discovery Systems"; In: B. Boulay, D. Hogg, L. Steels (eds.): Advances in Artificial Intelligence II (7th ECAI-86, Brighton, England, 1986), Elsevier Pub. (North Holland), Amsterdam, 1987, pp. 111–120
Habel, Ch. (82): "Inferences — The Base of Semantics?"; In: R. Bäuerle, C. Schwarze, A. v.Stechow (eds.): Meaning, Use and Interpretation of Language, deGruyter, Berlin, 1983
Habel, Ch. (86): "Prinzipien der Referentialität — Untersuchungen zur propositionalen Struktur von Wissen"; Informatik-Fachbericht 122, Springer, Berlin, 1986
Habel, Ch./ Rollinger, C.-R. (82): "The Machine as Concept Learner"; In: Proc. of the ECAI-82, Orsay, Frankreich, 1982
Holte, R.C. (86): "Alternative Information Structures in Incremental Learning Systems; To appear in: Y. Kodratoff, A. Hutchinson (eds.): Machine and Human Learning, Horwood Pub.
Hayes-Roth, F. (83): "Using Proofs and Refutations to Learn from Experience"; In: R.S. Michalski/ J.G. Carbonell/ T.M. Mitchell (eds.): Machine Learning, Tioga, Palo Alto, 1983, pp.221–240
Kauffman, H./ Grumbach, A. (86): "MULTILOG: Multiple Worlds in Logic Programming"; In: B. Boulay, D. Hogg, L. Steels (eds.): Advances in Artificial Intelligence II (7th ECAI-86, Brighton, England, 1986), Elsevier Pub. (North Holland), Amsterdam, 1987, pp. 233–247
Langley, P./ Gennari, J.H./ Iba, W. (87): "Hill-Climbing Theories of learning"; In: Proceedings of the Fourth International Workshop on Machine Learning, Irvine, California, Morgan Kaufmann, Los Altos, CA, 1987, pp. 312–323
Lebowitz, M. (87): "Experiments with Incremental Concept Formation: UNIMEM"; In: Machine Learning 2(2), 1987, pp. 103–138
Lenat, D.B. (82): "AM: Discovery in Mathematics as Heuristic Search"; In: R. Davis/D.G. Lenat: Knowledge Based Systems in Artificial Intelligence"; McGraw Hill, New York, 1982
Lenat, D. (83): "The Role of Heuristics in Learning by Discovery: Three Case Studies"; In: R.S. Michalski/J.G. Carbonell/T.M. Mitchell (eds.): Machine Learning, Tioga, 1983, pp. 243–306
McAllester, D.A. (82): "Reasoning Utility Package — User's Manual"; MIT, Memo 667, 1982
McDermott, D. (83): "Contexts and Data Dependencies: A Synthesis"; In: IEEE Transactions of Pattern Analysis and Machine Intelligence, Vol. PAMI-5, No. 3, May, 1983, pp. 237–246
Michalski, R.S./ Winston, P.H. (86): "Variable Precision Logic"; Artificial Intelligence, Vol. 29, 1986, pp. 121–146
Mitchell, T.M./ Utgoff, P.E./ Banerji, R. (83): "Learning by Experimentation: Acquiring and Refining Problem-Solving Heuristics"; In: R.S. Michalski/ J. Carbonell/ T.M. Mitchell (eds.): Machine Learning; Tioga Press, Palo Alto, CA, 1983, pp. 163–190
Morik, K. (87): "Acquiring Domain Models"; In: International Journal of Man-Machine Studies, 26, 1987, pp. 93–104
Morik, K. (88): "Sloppy Modeling"; In this volume
Morik, K./ Rollinger, C.-R. (85): "The Real Estate Agent — Modeling Users by Uncertain Reasoning"; In: The AI Magazine, Summer 1985; pp. 44–52
Neches, R./ Swartout, W.R./ Moore, J. (85): "Explainable (and Maintainable) Expert Systems"; In: Proceedings IJCAI-85, Los-Angeles, CA, 1985, pp. 382–389
Reinke, R.E./ Michalski, R.S. (85): "Incremental Learning of Concept Descriptions: A Method and Experimental Results"; In: Michie, D. (Ed.): Machine Intelligence XI, 1986.
Reiter, R. (80): "A Logic for Default Reasoning"; In: Artificial Intelligence 13(1,2), 1980, pp. 81–132
Rendell, L. (85): "Utility Patterns as Criteria for Efficient Generalization Learning"; Report UIUCDCS-R-85-1209, Department of Computer Science, University of Illinois at Urbana-Champaign, April 1985
Rollinger, C.-R. (83): "How to Represent Evidence — Aspects of Uncertain Reasoning"; In: Proc. IJCAI-83, Karlsruhe, 1983
Rollinger, C.-R. (84): "Die Repräsentation natürlichsprachlich formulierten Wissens — Behandlung der Aspekte Unsicherheit und Satzverknüpfung"; Dissertation, Fachbereich Informatik, Technische Universität Berlin, 1984
Rose, D./ Langley, P. (87): "Chemical Discovery as Belief Revision"; Machine Learning, Volume 1, 1986, pp. 423–451
Russell, S.E. (85): "The Complete Guide to MRS"; Report No. KSL-85-12, Stanford University, CA, 1985
Sammut, C. (88): "Logic Programs as a Basis for Machine Learning"; In: P. Brazdil (ed.): Proceedings of the Workshop on Machine Learning, Meta reasoning and Logics (Sesimbra, Portugal, 1988)
Schlimmer, J.C./ Granger, R.H. (86): Machine Learning, 1(3), 1986, pp. 317–354
Someren, M. W. van (88): "Using Dependencies between Attributes for Rule Learning"; In this volume
Thieme, S. (88): "The Acquisition of Model-Knowledge for a Model-Driven Machine Learning Approach"; In this volume
Wrobel, S. (87a): "Design Goals for Sloppy Modeling Systems"; To appear in: International Journal of Man-Machine Studies
Wrobel, S. (87b): "Higher-order Concepts in a Tractable Knowledge Representation"; In: Procs. 11th German Workshop on Artificial Intelligence 87, Springer, Berlin 1987
Wrobel, S. (88): "Demand-Driven Concept Formation"; In this volume
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 1989 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Emde, W. (1989). An inference engine for representing multiple theories. In: Morik, K. (eds) Knowledge Representation and Organization in Machine Learning. Lecture Notes in Computer Science, vol 347. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0017221
Download citation
DOI: https://doi.org/10.1007/BFb0017221
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-50768-0
Online ISBN: 978-3-540-46081-7
eBook Packages: Springer Book Archive