Abstract
While most approaches to similarity assessment are oblivious of knowledge and goals, there is ample evidence that these elements of problem solving play an important role in similarity judgements. This paper is concerned with an approach for integrating assessment of similarity into a framework of problem solving that embodies central notions of problem solving like goals, knowledge and learning. We review empirical findings that unravel characteristics of similarity assessment most of which have not been covered by purely syntactic models of similarity. A formal account of similarity assessment that allows for the integration of central ideas of problem solving is developed. Given a goal and a domain theory, an appropriate perspective is taken that brings into focus only goal-relevant features of a problem description as input to similarity assessment.
This research was supported by the “Deutsche Forschungsgemeinschaft” (DFG), “Sonderforschungsbereich” (SFB) 314: “Artificial Intelligence and Knowledge-Based Systems”, projects X9 and D3.
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References
L. W. Barsalou. Context-independent and context-dependent information in concepts. Memory & Cognition, 10:82–93, 1982.
J. D. Bransford, J. F. Franks, N. J. Vye, and R. D Sherwood. New approaches to instruction: because wisdom can't be told. In Stella Vosniadou and Andrew Ortony, editors, Similarity and Analogical Reasoning, pages 470–497. Cambridge University Press, 1989.
R. Barletta and W. Mark. Explanation-based indexing of cases. In Proceedings of 7 th National Conference on Artificial Intelligence. Minneapolis, 1988.
M. T. Chi, P. J. Feltovich, and R. Glaser. Categorization and representation of physics problems by experts and novices. Cognitive Science, 5:121–152, 1981.
A. Clement. Spontaneous analogies in problem solving: The progressive construction of mental models. In Proc. Meeting of the American Education Research Association, New York, 1982.
Timothy Cain, Michael J. Pazzani, and Glenn Silverstein. Using domain knowledge to influence similarity judgements. In Ray Bareiss, editor, Proc. of the 1991 Workshop on CBR, Washington D.C.,USA, May 1991. DARPA, Morgan Kaufmann Publishers.
L. R. Dice. Measures of the amount of ecologic association between species. Journal of Ecology, 26:297–302, 1945.
J. Fanes and B. Reiser. Access and use of previous solutions in a problem solving situation. In Proc. of the tenth Annual Conference of the Cognitive Science Society, pages 433–439, Montreal, 1988.
K. J. Holyoak and K. Koh. Surface and structural similarity in analogical transfer. Memory & Cognition, 15:332–340, 1987.
K.J. Holyoak. The pragmatics of analogical transfer. In G. Bower, editor, The psychology of learning and motivation. Academic Press, New York, NY, 1985.
S. Kedar-Cabelli. Purpose-directed analogy. In Proc. of the Cognitive Science Society, Irvine, CA, August 1985.
Janet L. Kolodner. Improving human decision making through case-based decision aiding. AI Magazine, 91(2):52–68, 1991.
E. Melis. Study of modes of analogical reasoning. Tasso-Report Nr. 5, Gesellschaft für Mathematik und Datenverarbeitung mbH (GMD), 1990.
T. M. Mitchell, R. M. Keller, and S. T. Kedar-Cabelli. Explanation-based generalization: A unifying view. Machine Learning, 1(1), 1986.
G. Polya. How to solve it. Princeton University Press, Princeton, NJ, 1945.
S. J. Russell. The use of Knowledge in Analogy and Induction. Pitman Publishing, London, 1989.
Michael M. Richter and Stefan Wess. Similarity, uncertainty and case-based reasoning in PATDEX. In Robert S. Boyer, editor, Automated Reasoning, Essays in Honor of Woody Bledsoe, pages 249–265. Kluwer Academic Publishing, 1991.
F. Schmalhofer, R. Bergmann, O. Kühn, and G. Schmidt. Using integrated knowledge acquisition to prepare sophisticated expert plans for their reuse in novel situations. In Proc. KAW-91, Banff, Canada, 1991.
C. Seifert, G. McKoon, R. Abelson, and R. Ratcliff. Memory connections between thematically similar episodes. J. Exp. Psych. Learning Memory Cognition, 12:220–231, 1986.
Linda B. Smith. From global similarities to kinds of similarities: the construction of dimensions in development. In Stella Vosniadou and Andrew Ortony, editors, Similarity and Analogical Reasoning, pages 146–178. Cambridge University Press, 1989.
G. Strube. Dynamic perspective in distributed representations. Zeitschrift fuer Psychologie, 199(4/91):289–298, 1991.
A. Tversky. Features of similarity. Psychological Review, 84:327–352, 1977.
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© 1993 Springer-Verlag Berlin Heidelberg
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Janetzko, D., Wess, S., Melis, E. (1993). Goal-driven similarity assessment. In: Jürgen Ohlbach, H. (eds) GWAI-92: Advances in Artificial Intelligence. Lecture Notes in Computer Science, vol 671. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0019013
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DOI: https://doi.org/10.1007/BFb0019013
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