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References

  1. Bateson, Gregory (1979),Mind and Nature: A Necessary Unity, New York Dutton.

  2. Boose, John H. (1985), ‘A Knowledge Acquisition Program for Expert Systems Based on Personal Construct Psychology’,International Journal of Man-Machine Studies 23: 495–525.

    Google Scholar 

  3. Bradshaw, Jeff M. and Boose, John H. (1990), ‘Decision Analytic Techniques for Knowledge Acquisition: Combining Information and Preference Models using Acquinas and Axotl’,International Journal of Man-Studies 32: 121–186.

    Google Scholar 

  4. Chi, Michelene T.H., Feltovich,Paul, and Glaser, Robert (1981), ‘Categorization and Representation of Physics Problems by Experts and Novices’,Cognitive Science 5: 121–152.

    Google Scholar 

  5. Dreyfus, Hubert L. (1979),What Computers Can't Do: The Limits of Artificial Intelligence;revised edition, New York: Harper & Row.

    Google Scholar 

  6. Ford, Ken M., Petry, Frederick E., Adams-Webber, Jack R., and Chang, Paul J. (1991), An Approach to Knowledge Acquisition Based on the Structure of Personal Construct Systems’,IEEE Transactions on Knowledge and Data Engineering 3: 78–88.

    Google Scholar 

  7. Kelly, George A. (1955),The Psychology of Personal Constructs, New York: Norton.

    Google Scholar 

  8. Gaines, Brian R. and Shaw, Mildred L.G. (1981), ‘New Directions in the Analysis and Interactive Elicitation of Personal Construct Systems’, in M.L.G. Shaw, ed.,Recent Advances in Personal Construct Technology, New York: Academic Press, pp. 147–182.

    Google Scholar 

  9. LaFrance, Marianne (1987), “The Knowledge Acquisition Grid: A Method for Training Knowledge Engineers’, Special Issue: Knowledge Acquisition for Knowledge-Based Systems, II,International Journal of Man-Machine Studies 26: 245–255.

    Google Scholar 

  10. Maturana, H.R., Lettvin, J., McCulloch, W., and Pitts, W. (1960), ‘Anatomy and Physiology of Vision in the Frog’,Journal of General Physiology 43: 129–175.

    Google Scholar 

  11. Ortony, Andrew (1975), ‘Why Metaphors Are Necessary and Not Just Nice’,Educational Theory 25: 45–53.

    Google Scholar 

  12. Schön, Donald A. (1979), ‘Generative Metaphor: A Perspective on Problem Setting in Social Policy’, in A. Ortony, ed.,Metaphor and Thought, Cambridge, UK: Cambridge University Press, pp. 254–283.

    Google Scholar 

  13. von Foerster, Heinz (1980), ‘Epistemology of Communication’, in K. Woodward, ed.,The Myths of Information: Technology and Post-Industrial Culture. Madison, WI: Coda Press, pp. 18–27.

    Google Scholar 

  14. von Foerster, Heinz (1981),Observing Systems, Seaside, CA: Intersystems Publications.

    Google Scholar 

  15. Winograd, Terry and Flores, Fernando (1987),Understanding Computers and Cognition, Norwood, NJ: Ablex Publishing.

    Google Scholar 

References

  1. Barron, A. and Cover, T. (1991), ‘Minimum Complexity Density Estimation’,IEEE Transactions on Information Theory, Vol. 37, No. 4.

    Google Scholar 

  2. Berger, J. O. (1985),Statistical Decision Theory and Bayesian Analysis, New York: Springer-Verlag.

    Google Scholar 

  3. Buntine, W. (1989), ‘A Critique of the Valiant Model’,Proceedings of the 11th International Joint Conference on Artificial Intelligence (IJCAI-89, Detroit), San Mateo, CA: Morgan Kaufmann, pp. 837–842.

    Google Scholar 

  4. Buntine, W. (1992), ‘Learning Classification Trees’, in D. Hand, (ed.),Artificial Intelligence and Statistics, London: Chapman and Hall, to appear.

    Google Scholar 

  5. Carbonell, J. (ed.) (1990),Machine Learning: Paradigms and Methods, Cambridge, MA: MIT Press.

    Google Scholar 

  6. Devroye, L. (1987),A Course in Density Estimation. Boston: Birkhauser.

    Google Scholar 

  7. Levi, E., Tishby, N., and Solla, S. (1989), ‘A Statistical Approach to Learning and Generalization in Layered Neural Networks’, in R. Rivest et al. (eds.),Proceedings of the 2nd Workshop on Computational Learning Theory (COLT-89, University of California at Santa Cruz), San Mateo, CA: Morgan Kaufmann, pp. 245–260.

    Google Scholar 

  8. Minton, S. (1988), ‘Quantitative Results Concerning the Utility of Explanation-Based Learning’,Proceedings of the 7th National Conference on Artificial Intelligence (AAAI-88; St. Paul, MN), San Mateo, CA: Morgan Kaufmann, pp. 564–569.

    Google Scholar 

  9. Opper, M., and Haussler, D. (1991), ‘Calculation of the Learning Curve of Bayes Optimal Classification Algorithm for Learning a Perceptron with Noise’,Proceedings of the 1991 Workshop on Computational Learning Theory (COLT-91), San Mateo, CA: Morgan Kaufmann.

    Google Scholar 

  10. Shavlik, J., and Dietterich, T. (eds.) (1990),Readings in Machine Learning, San Mateo, CA: Morgan Kaufmann.

    Google Scholar 

  11. Sompolinski, H. S., Seung, H., and Tishby, N. (1991), ‘Learning Curves in Large Neural Networks’,Proceedings of the 1991 Workshop on Computational Learning Theory (COLT-91), San Mateo, CA: Morgan Kaufmann.

    Google Scholar 

  12. Sridharan, N. S. (ed.) (1989),Proceedings of the 11th International Joint Conference on Artificial Intelligence (IJCAI-89, Detroit), San Mateo, CA: Morgan Kaufmann.

    Google Scholar 

  13. van Harmelen, F., and Bundy, A. (1988), ‘Explanation-Based Generalisation = Partial Evaluation’,Artificial Intelligence 36: 401–412.

    Google Scholar 

  14. Vapnik, V. (1982),Estimation of Dependencies Based on Empirical Data, New York: Springer-Verlag.

    Google Scholar 

References

  1. Black, Max (1962),Models and Metaphors, Ithaca, NY: Cornell University Press.

    Google Scholar 

  2. Carbonell, Jaime G. (1981), ‘Metaphor: An Inescapable Phenomenon in Natural-Language Comprehension’, in W.G. Lehnert and M.H. Ringle, eds.,Strategies for Natural Language Processing, Hillsdale, NJ: Lawrence Erlbaum, pp. 415–434.

    Google Scholar 

  3. Gentner, Dedre (1985), ‘Structure-Mapping: A Theoretical Framework for Analogy’,Cognitive Science 7 pp. 155–170.

    Google Scholar 

  4. Lakoff, George and Johnson, Mark (1980),Metaphors We Live By, Chicago: University of Chicago Press.

    Google Scholar 

  5. Lakoff, George and Turner, Mark (1989),More than Cool Reason: A Field Guide to Poetic Metaphor, Chicago: University of Chicago Press.

    Google Scholar 

  6. MacCormac, Earl R. (1985),A Cognitive Theory of Metaphor, Cambridge, MA: MIT Press.

    Google Scholar 

  7. Martin, James H. (1990),A Computational Model of Metaphor, Boston: Academic Press.

    Google Scholar 

  8. Ortony, Andrew (1980), ‘Some Psycholinguistic Aspects of Metaphor’, in R. Honeck and R. Hoffman, eds.,Cognitive and Figurative Language, Hillsdale, NJ: Lawrence Erlbaum, pp. 69–83.

    Google Scholar 

  9. Searle, John R. (1959), ‘On Determinables and Resemblances’, part II,Proceedings of the Aristotelian Society, Supp. 33, pp. 141–158.

    Google Scholar 

  10. Searle, John R. (1967), ‘Determinables and Determinates’, in P. Edwards, ed.,Encyclopedia of Philosophy, New York: Free Press, Vol. 1, pp. 357–359.

    Google Scholar 

  11. Sowa, John F. (1984),Conceptual Structures: Information Processing in Mind and Machine, Reading, MA: Addison-Wesley.

    Google Scholar 

  12. Tourangeau, Roger, and Sternberg, Robert J. (1982), ‘Understanding and Appreciating Metaphors’,Cognition 11, pp. 203–244.

    Google Scholar 

References

  1. Bennett, Bruce M., Hoffman, Donald D., and Prakash, Chetan (1989),Observer Mechanics: A Formal Theory of Perception, San Diego: Academic Press.

    Google Scholar 

  2. Berwick, Robert (1985),The Acquisition of Syntactic Knowledge, Cambridge, MA: MIT Press.

    Google Scholar 

  3. Chomsky, Noam (1965),Aspects of the Theory of Syntax, Cambridge, MA: MIT Press.

    Google Scholar 

  4. Foster, John A. (1976), ‘Meaning and Truth Theory,’ in G. Evans and J. McDowell, eds.,Truth and Meaning, Oxford: Oxford University Press, pp. 1–32.

    Google Scholar 

  5. Higginbotham, James (1990), ‘Truth and Understanding,’Iyyun 40: 271–288; abridged version inPhilosophical Studies 65 (1992), 3–16.

    Google Scholar 

  6. Tversky, Amos (1977), ‘Features of Similarity,’Psychological Review 84: 327–352.

    Google Scholar 

References

  1. Ballim, A. and Wilks, Y. (1991),Artificial Believers, Hillsdale, NJ: Lawrence Erlbaum Associates.

    Google Scholar 

  2. Ballim, A.; Wilks, Y.; and Barnden, J. (1991), ‘Belief, Metaphor, and Intensional Identification’,Cognitive Science 15: 133–171.

    Google Scholar 

  3. Fauconnier, G. (1985),Mental Spaces: Aspects of Meaning Construction in Natural Language, Cambridge, MA: MIT Press.

    Google Scholar 

  4. Johnson-Laird, P. N. (1983),Mental Models, Cambridge, Eng.: Cambridge University Press.

    Google Scholar 

  5. Lakoff, G. (1987),Women, Fire, and Dangerous Things: What Categories Reveal about the Mind, Chicago: University of Chicago Press.

    Google Scholar 

  6. Maida, A. S. (1991), ‘Maintaining Models of Agents Who Have Existential Misconceptions’,Artificial Intelligence 50: 331–383.

    Google Scholar 

  7. Winograd, T. and Flores, F. (1986),Understanding Computers and Cognition, Norwood, NJ: Ablex.

    Google Scholar 

References

  1. Maida, Anthony S. (1991), ‘Maintaining Mental Models of Agents Who Have Existential Misconceptions,’Artificial Intelligence 50: 331–383.

    Google Scholar 

  2. Meehan, James Richard (1976),The Metanovel: Writing Stories by Computer, (Ph.D. dissertation, Yale University, December 1976).

  3. Moore, Robert C. (1973), ‘D-script: A Computational Theory of Descriptions,’Proceedings of the 3rd International Joint Conference on Artificial Intelligence (IJCAI-73, Stanford University), Los Altos, CA: William Kaufmann, pp. 223–229.

    Google Scholar 

References

  1. Miikulainen, Risto and Dyer, Michael G. (1991), ‘Natural Language Processing with Modular PDP Networks and Distributed Lexicon’,Cognitive Science 15, pp. 343–399.

    Google Scholar 

  2. St. John, Mark F. (1992), ‘The Story Gestalt: A Model of Knowledge-Intensive Processes in Text Comprehension’,Cognitive Science 16, pp. 271–306.

    Google Scholar 

References

  1. Caplan, D. (1987),Neurolinguistics and Linguistic Aphasiology, Cambridge, MA: MIT Press.

    Google Scholar 

  2. Caplan, D. and Hildebrandt, N. (1988),Disorders of Syntactic Comprehension, Cambridge, MA: MIT Press.

    Google Scholar 

  3. Churchland, P. S. and Sejnowski, T. J. (1992),The Computational Brain, Cambridge, MA: MIT Press.

    Google Scholar 

  4. Damasio, A. R. (1989a), ‘The Brain Binds Entities and Events by Multiregional Activation from Convergence Zones’,Neural Computation 1: 123–132.

    Google Scholar 

  5. Damasio, A. R. (1989b), ‘Concepts in the Brain’,Mind and Language 4: 24–28.

    Google Scholar 

  6. Damasio, A. R. (1989c), ‘Time-locked Multiregional Retroactivation: A Systems-Level Proposal for the Neural Substrates of Recall and Recognition’,Cognition 33: 25–62.

    Google Scholar 

  7. Dennett, D. C. (1992),Consciousness Explained, Boston, MA: Little, Brown.

    Google Scholar 

  8. Edelman, G. M. (1989),The Remembered Present: A Biological Theory of Consciousness. New York: Basic Books.

    Google Scholar 

  9. Felleman, D. J. and Van Essen, D. C. (1991), ‘Distributed Hierarchical Processing in Primate Cerebral Cortex’,Cerebral Cortex 1: 1–47.

    Google Scholar 

  10. Grodzinsky, Y. (1990),Theoretical Perspectives on Language Deficits, Cambridge, MA: MIT Press.

    Google Scholar 

  11. Hummel, J. E. and Biederman, I. (1992), ‘Dynamic Binding in a Neural Network for Shape Recognition’,Psychological Review 99: 480–517.

    Google Scholar 

  12. Kean M.-L. (ed.) (1985),Agrammatism, New York: Academic Press.

    Google Scholar 

  13. Kosslyn, S. M., Chabris, C.F., Marsolek, C. J., and Koenig, O. (in press), ‘Categorical Versus Coordinate Spatial Representations: Computational Analyses and Computer Simulations’,Journal of Experimental Psychology: Human Perception and Performance.

  14. Kosslyn, S. M., Flynn, R. A., Amsterdam, J. B., and Wang, G. (1990), ‘Components of High-Level Vision: A Cognitive Neuroscience Analysis and Accounts of Neurological Syndromes’,Cognition 34: 203–277.

    Google Scholar 

  15. Kosslyn, S. M. and Intriligator, J. M. (1992), ‘Is Cognitive Neuropsychology Plausible? The Perils of Sitting on a One-Legged Stool’,Journal of Cognitive Neuroscience 4: 96–106.

    Google Scholar 

  16. Kosslyn, S. M. and van Kleeck, M. (1990), ‘Broken Brains and Normal Minds: Why Humpty-Dumpty Needs a Skeleton’, in E. L. Schwartz (ed.),Computational Neuroscience, Cambridge, MA: MIT Press, pp. 390–402.

    Google Scholar 

  17. Lehky, S. R. and Sejnowski, T. J. (1988), ‘Network Model of Shape-from-Shading: Neural Function Arises from both Receptive and Projective Fields’,Nature 333: 452–454.

    Google Scholar 

  18. Mumford, D. (1992), ‘On the Computational Architecture of the Neocortex: II. The Role of Cortico-Cortical Loops’,Biological Cybernetics 66: 241–251.

    Google Scholar 

  19. Plaut, D. C. and Shallice, T. (1991), ‘Effects of Word Abstractness in a Connectionist Model of Deep Dyslexia’,Proceedings of the 13th Annual Meeting of the Cognitive Science Society (University of Chicago), Hillsdale, NJ: Lawrence Erlbaum Associates, pp. 73–78.

    Google Scholar 

  20. Rueckl, J. G., Cave, K. R., and Kosslyn, S. M. (1989), ‘Why Are “What” and “Where” Processed by Separate Cortical Systems? A Computational Investigation’,Journal of Cognitive Neuroscience 1: 171–186.

    Google Scholar 

  21. Shallice, T. (1991), ‘Précis ofFrom Neuropsychology to Mental Structure’,Behavioral and Brain Sciences 14: 429–437.

    Google Scholar 

  22. Shepard, G. (1990), ‘The Significance of Real Neuron Architectures for Neural Network Simulations’, in E. L. Schwartz (ed.),Computational Neuroscience, Cambridge, MA: MIT Press, pp. 82–96.

    Google Scholar 

  23. Sporns, O., Gally, J. A., Reeke, G. N., Jr., and Edelman, G. M. (1989), ‘Reentrant Signaling among Simulated Neuronal Groups Leads to Coherency in Their Oscillatory Activity,’Proceedings of the National Academy of Science 86: 7265–7269.

    Google Scholar 

References

  1. Hatfield, Gary (1988), ‘Representation and Content in Some (Actual) Theories of Perception’,Studies in History and Philosophy of Science 19, pp. 175–214.

    Google Scholar 

  2. Hatfield, Gary (1991), ‘Representation in Perception and Cognition: Connectionist Affordances’, in W. Ramsey, S. Stich, and D. Rumelhart, eds.,Philosophy and Connectionist Theory, Hillsdale, NJ: Lawrence Erlbaum Associates, pp. 163–195.

    Google Scholar 

  3. Kosslyn, Stephen (1980),Image and Mind, Cambridge, MA: Harvard University Press.

    Google Scholar 

  4. Kosslyn, Stephen (1983),Ghosts in the Mind's Machine, New York: W.W. Norton.

    Google Scholar 

  5. Kosslyn, Stephen and Hatfield, Gary (1984), ‘Representation without Symbol Systems’,Social Research 51, pp. 1019–1045.

    Google Scholar 

  6. Kosslyn, Stephen; Pinker, Steven; Smith, George; and Schwartz, Steven (1979), ‘On the Demystification of Mental Imagery’,The Behavioral and Brain Sciences 2, pp. 535–581.

    Google Scholar 

  7. Moran, Thomas (1979), ‘The Imprecision of Mental Imagery’,The Behavioral and Brain Sciences 2, p. 560.

    Google Scholar 

  8. Pinker, Steven (1980), ‘Mental Imagery and the Third Dimension’,Journal of Experimental Psychology: General 109, pp. 354–371.

    Google Scholar 

  9. Pinker, Steven and Finke, Ronald (1980), ‘Emergent Two-Dimensional Patterns in Images Rotated in Depth’,Journal of Experimental Psychology: Human Perception and Performance 6, pp. 244–264.

    Google Scholar 

  10. Shapiro, Lawrence (1992),Representational Content in Cognitive Psychology, Ph.D. dissertation, Philadelphia: University of Pennsylvania Department of Philosophy.

    Google Scholar 

  11. Shapiro, Lawrence (forthcoming), ‘Behavior, ISO Functionalism, and Psychology’,Studies in History and Philosophy of Science.

  12. Von Eckardt, Barbara (1984), ‘Cognitive Psychology and Principled Skepticism,Journal of Philosophy 81, pp. 67–88.

    Google Scholar 

References

  1. Bratman, Michael E. (1987),Intentions, Plans, and Practical Reason, Cambridge, MA: Harvard University Press.

    Google Scholar 

  2. Davidson, Donald (1980), ‘Agency’, inEssays on Actions and Events, Oxford: Clarendon Press.

    Google Scholar 

References

  1. Bringsjord, Selmer (1991), ‘Is the Connectionist-Logicist Clash One of AI's Wonderful Red Herrings?’,Journal of Experimental and Theoretical Artificial Intelligence 3: 319–349.

    Google Scholar 

  2. Bringsjord, Selmer (1992),What Robots Can and Can't Be, Dordrecht: Kluwer Academic Publishers.

    Google Scholar 

  3. Bringsjord, Selmer (1994), ‘Searle on the Brink’,Psyche 1(5) [32 paragraphs], URL: ftp://hcrl.open.ac.uk/pub/psyche/volume1/psyche-94-1-5-propertydualism-1-bringsjord.txt

  4. Bringsjord, Selmer (1994), ‘Computation, among Other Things, Is beneath Us’,Minds and Machines 4: 467–486.

    Google Scholar 

  5. Bringsjord, Selmer, and Zenzen, M. (forthcoming),In Defense of Non-Algorithmic Cognition, Dordrecht: Kluwer Academic Publishers.

  6. Chisholm, Roderick M. (1978), ‘Is There a Mind Body Problem?’,Philosophic Exchange 2: 25–32.

    Google Scholar 

  7. Churchland, Paul (1984),Matter and Consciousness, Cambridge, MA: MIT Press.

    Google Scholar 

  8. Dennett, Daniel (1991),Consciousness Explained, Boston: Little, Brown.

    Google Scholar 

  9. Eccles, John C. and Popper, Karl (1977),The Self and Its Brain, New York: Springer-Verlag.

    Google Scholar 

  10. Lettvin, J.Y., Maturama, H.R., McCulloch, W.S., and Pitts, W.H. (1959), ‘What the Frog's Eye Tells the Frog's Brain’,Proceedings of the Institute of Radio Engineers 47: 1940–1951.

    Google Scholar 

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Authors and Affiliations

  1. Department of Industrial Engineering and Center for Cognitive Science, State University of New York at Buffalo, 14260, Buffalo, NY, USA

    Valerie L. Shalin

  2. Research Institute for Advanced Computer Science and Artificial Intelligence Research Branch, NASA Ames Research Center, MS 269-2, 94035, Moffett Field, CA, USA

    Wray L. Buntine

  3. Department of Philosophy, University of Cincinnati, 45221, Cincinnati, OH, USA

    S. Gillian Parker

  4. Sommerville College, Oxford University, OX2 6HD, Oxford, ENGLAND

    James Higginbotham

  5. Institut Dalle Molle pour les Études Sémantiques et Cognitives (ISSCO), Université de Genève, Route des Acacias, 54, CH-1227, Geneva, Switzerland

    Afzal Ballim

  6. Center for Advanced Computer Studies, University of Southwestern Louisiana, 70504-4330, Lafayette, LA, USA

    Anthony S. Maida

  7. Department of Psychology, University of Minnesota, 75 East River Road, 55455-0344, Minneapolis, MN, USA

    Charles R. Fletcher

  8. Department of Linguistics and Center for Cognitive Science, State University of New York at Buffalo, 14260, Buffalo, NY, USA

    David L. Kemerer

  9. Department of Philosophy, University of Wisconsin-Madison, 53706, Madison, WI, USA

    Lawrence A. Shapiro

  10. Department of Mathematics and Computer Science, West Chester University, 19383, West Chester, PA, USA

    Richard Wyatt

  11. Department of Mathematics, Bryn Mawr College, 19010, Bryn Mawr, PA, USA

    Deepak Kumar

  12. Department of Philosophy, Psychology, and Cognitive Science, Department of Computer Science, Renssalaer Institute of Technology, 12180, Troy, NY, USA

    Selmer Bringsjord & Bill Patterson

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Shalin, V.L., Buntine, W.L., Parker, S.G. et al. Book reviews. Mind Mach 5, 257–307 (1995). https://doi.org/10.1007/BF00974747

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