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Two Ways of Analogy: Extending the Study of Analogies to Mathematical Domains

Published online by Cambridge University Press:  01 January 2022

Abstract

The structure-mapping theory has become the de facto standard account of analogies in cognitive science and philosophy of science. In this paper I propose a distinction between two kinds of domains and I show how the account of analogies based on structure-preserving mappings fails in certain (object-rich) domains, which are very common in mathematics, and how the axiomatic approach to analogies, which is based on a common linguistic description of the analogs in terms of laws or axioms, can be used successfully to explicate analogies of this kind. Thus, the two accounts of analogies should be regarded as complementary, since each of them is adequate for explicating analogies that are drawn between different kinds of domains. In addition, I illustrate how the account of analogies based on axioms has also considerable practical advantages, for example, for the discovery of new analogies.

Type
Research Article
Copyright
Copyright © The Philosophy of Science Association

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Footnotes

I would like to thank Brian van den Broek, Clark Glymour, Michael Hallett, Brigitte Pientka, and an anonymous reviewer for many discussions and comments. Earlier versions of this paper were presented at the 2004 meeting of the Canadian Philosophical Association in Winnipeg, MB, and at the conference on Philosophical Perspectives on Scientific Understanding, held in August 2005 in Amsterdam, the Netherlands. I am grateful to the various participants for discussions and comments. Work on this paper was supported by the Social Sciences and Humanities Research Council of Canada.

References

REFERENCES

Aronson, Jerrold L., Harré, Rom, and Way, Eileen C. (1995), Realism Rescued: How Scientific Progress Is Possible. LaSalle, IL: Open Court.Google Scholar
Boltzmann, Ludwig (1911), “Model”, in Encyclopedia Britannica, Vol. 18. Cambridge: Cambridge University Press, 638640.Google Scholar
Bourbaki, Nicholas (1950), “The Architecture of Mathematics”, The Architecture of Mathematics 57:221232.Google Scholar
Colton, Simon, Bundy, Alan, and Walsh, Toby (1999), “Automatic Concept Formation in Pure Mathematics”, in Dean, Thomas (ed.), Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence. San Francisco: Morgan Kaufmann, 786793.Google Scholar
Colton, Simon, Meier, Andreas, Sorge, Volker, and McCasland, Roy L. (2004), “Automatic Generation of Classification Theorems for Finite Algebras”, in Basin, David A. and Rusinowitch, Michaël (eds.), Automated Reasoning—Second International Joint Conference. Lecture Notes in Computer Science, vol. 3097. Berlin: Springer, 400414.CrossRefGoogle Scholar
Corry, Leo (1996), Modern Algebra and the Rise of Mathematical Structures. Science Networks: Historical Studies, vol. 17. Basel: Birkhäuser.Google Scholar
Darden, Lindley, and Cain, Joseph A. (1989), “Selection Type Theories”, Selection Type Theories 56:106129.Google Scholar
Demopoulos, William, and Friedman, Michael (1985), “Critical Notice: Bertrand Russell's The Analysis of Matter: Its Historical Context and Contemporary Interest”, Critical Notice: Bertrand Russell's The Analysis of Matter: Its Historical Context and Contemporary Interest 52:621639.Google Scholar
Duhem, Pierre ([1906] 1954), The Aim and Structure of Physical Theory. Translated by Wiener, P. P.. Originally published as La théorie physique: Son objet, et sa structure (Paris: Marcel Rivière). Princeton, NJ: Princeton University Press.CrossRefGoogle Scholar
Falkenhainer, Brian, Forbus, Kenneth D., and Gentner, Dedre (1990), “The Structure-Mapping Engine: Algorithm and Examples”, The Structure-Mapping Engine: Algorithm and Examples 41:163.Google Scholar
Gentner, Dedre (1983), “Structure-Mapping: A Theoretical Framework for Analogy”, Structure-Mapping: A Theoretical Framework for Analogy 7:155170.Google Scholar
Gentner, Dedre, and Holyoak, Keith J. (1997), “Reasoning and Learning by Analogy. Introduction”, Reasoning and Learning by Analogy. Introduction 52:3234.Google Scholar
Gentner, Dedre, Holyoak, Keith J., and Kokinov, Boicho N., eds. (2001), The Analogical Mind—Perspectives from Cognitive Science. Cambridge, MA: MIT Press.CrossRefGoogle Scholar
Gentner, Dedre, and Jeziorski, Michael (1987), “Historical Shifts in the Use of Analogy in Science”. Technical Report UIUCDCD-R-87-1389, Department of Computer Science. Urbana: University of Illinois at Urbana-Champaign.Google Scholar
Gentner, Dedre, and Markman, Arthur B. (1997), “Structure Mapping in Analogy and Similarity”, Structure Mapping in Analogy and Similarity 52:4556.Google Scholar
Gentner, Dedre, and Markman, Arthur B. (2005), “Defining Structural Similarity”, Defining Structural Similarity 6:120.Google Scholar
Gentner, Dedre, and Wolff, P. (2000), “Metaphor and Knowledge Change”, in Dietrich, E. and Markman, A. (eds.), Cognitive Dynamics: Conceptual Change in Humans and Machines. Mahwah, NJ: Erlbaum, 295342.Google Scholar
Gick, Mary L., and Holyoak, Keith J. (1983), “Schema Induction and Analogical Transfer”, Schema Induction and Analogical Transfer 15:138.Google Scholar
Helman, David H., ed. (1988), Analogical Reasoning—Perspectives of Artificial Intelligence, Cognitive Science, and Philosophy. Synthese Library, vol. 197. Dordrecht: Kluwer Academic.Google Scholar
Hempel, Carl G. (1965), Aspects of Scientific Explanation and Other Essays in the Philosophy of Science. New York: Free Press.Google Scholar
Hesse, Mary B. (1966), Models and Analogies in Science. Notre Dame, IN: University of Notre Dame Press.Google Scholar
Hesse, Mary B. (1972), “Models and Analogy in Science”, in Edwards, Paul (ed.), Encyclopedia of Philosophy. New York: Macmillan, 354359.Google Scholar
Hilbert, David ([1918] 1996), “Axiomatisches Denken” (English translation), in William Ewald (ed.), From Kant to Hilbert: A Source Book in Mathematics. Originally published in Mathematische Annalen 78:405415. Oxford: Clarendon Press, 1105–1115.Google Scholar
Hilbert, David ([1899] 2004), Grundlagen der Geometrie. Reprinted in Michael Hallett and Ulrich Majer (eds.), David Hilbert's Lectures on the Foundations of Geometry, 1891–1902. Originally published as Grundlagen der Geometrie (Leipzig: Teubner). Berlin: Springer, 436525.Google Scholar
Hochwald, Scott H. (1991), “Linear Algebra by Analogy”, Linear Algebra by Analogy 98:918926.Google Scholar
Holyoak, Keith J., Gentner, Dedre, and Kokinov, Boicho N. (eds.) (1998), Advances in Analogy Research: Integration of Theory and Data from the Cognitive, Computational, and Neural Sciences. Sofia: New Bulgarian University.Google Scholar
Holyoak, Keith J., and Thagard, Paul (1989), “Analogical Mapping by Constraint Satisfaction”, Analogical Mapping by Constraint Satisfaction 13:295355.Google Scholar
Holyoak, Keith J., and Thagard, Paul (1997), “The Analogical Mind”, The Analogical Mind 52:3544.Google ScholarPubMed
Keane, Mark, and Brayshaw, M. (1988), “The Incremental Analogy Machine: A Computational Model of Analogy”, in Sleeman, Derek H. (ed.), Proceedings of the Third European Working Session on Learning. London: Pitman, 5362.Google Scholar
Keane, Mark T., Ledgeway, Tim, and Duff, Stuart (1994), “Constraints on Analogical Mapping: A Comparison of Three Models”, Constraints on Analogical Mapping: A Comparison of Three Models 18:387438.Google Scholar
Kedar-Cabelli, Smadar (1988), “Analogy—from a Unified Perspective”, in Helman 1988, 65104.Google Scholar
Keynes, John Maynard (1921), Treatise on Probability. London: Macmillan.Google Scholar
Knobloch, Eberhard (1989), “Analogie und Mathematisches Denken”, Analogie und Mathematisches Denken 12:3547.Google Scholar
Lakoff, George, and Johnson, Mark (2003), Metaphors We Live By. Chicago: University of Chicago Press.CrossRefGoogle Scholar
Lakoff, George, and Núñez, Raphael E. (2000), Where Mathematics Comes From: How the Embodied Mind Brings Mathematics into Being. New York: Basic Books.Google Scholar
Leatherdale, W. H. (1974), Analogy, Model and Metaphor in Science. Amsterdam: North-Holland.Google Scholar
Lenat, Douglas B. (1976), AM: An Artificial Intelligence Approach to Discovery in Mathematics as Heuristic Search. Ph.D. dissertation. Stanford, CA: Stanford University.Google Scholar
Lenat, Douglas B. (1983), “EURISKO: A Program Which Learns New Heurstics and Domain Concepts”, EURISKO: A Program Which Learns New Heurstics and Domain Concepts 21:6198.Google Scholar
Lenat, Douglas B., and Brown, J. S. (1984), “Why AM and EURISKO Appear to Work”, Why AM and EURISKO Appear to Work 23:269294.Google Scholar
Magnani, Lorenzo, and Nersessian, Nancy J., eds. (2002), Model-Based Reasoning: Science, Technology, Values. New York: Kluwer Academic.CrossRefGoogle Scholar
Maxwell, James Clerk ([1855] 1890), “On Faraday's Lines of Force”, in W. D. Niven (ed.), The Scientific Papers of James Clerk Maxwell. Originally published in Transactions of the Cambridge Philosophical Society 10:2783. Cambridge: Cambridge University Press, 155–229.CrossRefGoogle Scholar
Maxwell, James Clerk ([1870] 1890), “Address to the Mathematical and Physical Sections of the British Association”, in W. D. Niven (ed.), The Scientific Papers of James Clerk Maxwell. Originally published in British Association Report, vol. 40. Cambridge: Cambridge University Press, 215229.CrossRefGoogle Scholar
McCune, William (1992), “Automated Discovery of New Axiomatizations of the Left Group and Right Group Calculi”, Automated Discovery of New Axiomatizations of the Left Group and Right Group Calculi 9:124.Google Scholar
McCune, William, et al. (2002), “Short Single Axioms for Boolean Algebra”, Short Single Axioms for Boolean Algebra 29:116.Google Scholar
McKeon, Richard, ed. (1947), Introduction to Aristotle. New York: Random House.Google Scholar
Morrison, Margaret (2000), Unifying Scientific Theories. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Nagel, Ernest (1961), The Structure of Science: Problems in the Logic of Scientific Explanation. New York: Harcourt, Brace & World.CrossRefGoogle Scholar
Nersessian, Nancy J. (1992), “How Do Scientists Think? Capturing the Dynamics of Conceptual Change in Science”, in Giere, Ronald N. (ed.), Cognitive Models of Science. Minnesota Studies in the Philosophy of Science, vol. 15. Minneapolis: University of Minnesota Press, 344.Google Scholar
Newman, M. H. A. (1928), “Mr. Russell's ‘Causal Theory of Perception’”, Mr. Russell's ‘Causal Theory of Perception’ 37:137148.Google Scholar
Polya, George (1954), Mathematics and Plausible Reasoning. Induction and Analogy in Mathematics, vol. 1. Princeton, NJ: Princeton University Press.CrossRefGoogle Scholar
Polya, George (1981), Mathematical Discovery: On Understanding, Learning, and Teaching Problem Solving. New York: Wiley.Google Scholar
Poser, Hans (1989), “Vom Denken in Analogien”, Vom Denken in Analogien 12:145157.Google Scholar
Ritchie, G. D., and Hanna, F. K. (1984), “AM: A Case Study in AI Methodology”, AM: A Case Study in AI Methodology 23:248268.Google Scholar
Rotman, Joseph (1996), A First Course in Abstract Algebra. Upper Saddle River, NJ: Prentice-Hall.Google Scholar
Schlimm, Dirk (2006), “Axiomatics and Progress in the Light of 20th Century Philosophy of Science and Mathematics”, in Löwe, Benedikt, Peckhaus, Volker, and Räsch, Thoralf (eds.), Foundations of the Formal Sciences IV. Studies in Logic Series. London: College Publications, 233253.Google Scholar
Schlimm, Dirk (2008a), “Bridging Theories with Axioms: Boole, Stone, and Tarski”, in van Bendegem, J.-P. and Kerkhove, B. van (eds.), Perspectives on Mathematical Practices, vol. 2. Berlin: Springer, forthcoming.Google Scholar
Schlimm, Dirk (2008b), “On the Creative Role of Axiomatics: The Discovery of Lattices by Schröder, Dedekind, Birkhoff, and Others”, Synthese, forthcoming.CrossRefGoogle Scholar
Shelley, Cameron (2003), Multiple Analogies in Science and Philosophy. Amsterdam: Benjamins.CrossRefGoogle Scholar
Sterrett, Susan G. (1998), “Sounds Like Light: Einstein's Special Theory of Relativity and Mach's Work in Acoustics and Aerodynamics”, Sounds Like Light: Einstein's Special Theory of Relativity and Mach's Work in Acoustics and Aerodynamics 29:135.Google Scholar
Suppes, Patrick ([1960] 1969), “A Comparison of the Meaning and Uses of Models in Mathematics and the Empirical Sciences”, in Patrick Suppes, Studies in the Methodology and Foundations of Science: Selected Papers from 1951 to 1969. Originally published in Synthese 12:287301. Dordrecht: Reidel, 10–23.CrossRefGoogle Scholar
Thagard, Paul (1988), “Dimensions of Analogy”, in Helman 1988, 105124.Google Scholar
van der Waerden, Bartel L. (1930), Moderne Algebra. Berlin: Springer.CrossRefGoogle Scholar
van Rooij, Iris, Evans, Patricia, Müller, Moritz, Gedge, Jason, and Wareham, Todd (2008), “Identifying Sources of Intractability in Cognitive Models: An Illustration Using Analogical Structure Mapping”, in Love, B. C., McRae, K., and Sloutsky, V. M. (eds.), Proceedings of the 30th Annual Conference of the Cognitive Science Society. Austin, TX: Cognitive Science Society, 915-920.Google Scholar
Way, Eileen C. (1991), Knowledge Representation and Metaphor. Dordrecht: Kluwer.CrossRefGoogle Scholar
Way, Eileen C. (1992), “The Dynamic Type Hierarchy Theory of Metaphor”, in Nagle, Timothy E., Nagle, Janice A., Gerholz, Laurie L., and Eklund, Peter W. (eds.), Conceptual Structures: Current Research and Practice. Upper Saddle River, NJ: Horwood, 543557.Google Scholar
Wussing, Hans ([1969] 1984), The Genesis of the Abstract Group Concept. Translated by Abe Shenitzer. Originally published as Die Genesis des abstrakten Gruppenbegriffes (Berlin: Deutscher Verlag der Wissenschaften). Cambridge, MA: MIT Press.Google Scholar