Bibliography

H. R. Ekbia

doi:10.1017/CBO9780511802126.017

Agre, P. E. (1995). “The Soul Gained and Lost: Artificial Intelligence as A Philosophical Project.” Stanford Humanity Review 4(2).Google Scholar

Agre, P. E. (1997a). Computation and Human Experience. Cambridge, UK, Cambridge University Press.CrossRef Google Scholar

Agre, P. E. (1997b). Toward a Critical Technical Practice: Lessons Learned in Trying to Reform AI. Bridging the Great Divide: Social Science, Technical Systems, and Cooperative Work. G. Bowker, L. S. Star, B. Turner and L. Gasser. New York, NY, Erlbaum.Google Scholar

Agre, P. E. (2002). The Practical Logic of Computer Work. Computationalism: New Directions. M. Scheutz. Cambridge, UK, Cambridge University Press.Google Scholar

Agre, P. E. and , D. Chapman (1987). Pengi: An implementation of a theory of activity. Sixth National Conference on Artificial Intelligence, San Mateo, CA., Morgan Kaufmann.Google Scholar

Agre, P. E. and , I. D. Horswill (1992). Cultural Support for Improvisation. Tenth National Conference on Artificial Intelligence, Los Altos, CA., Morgan Kaufmann.Google Scholar

Agre, P. E. and , D. Schuler (1997). Reinventing Technology, Rediscovering Community: Critical Explorations of Computing as a Social Practice. New York, NY, Ablex.Google Scholar

Anderson, J. A (1995). An Introduction to Neural Networks. Cambridge, MA., A Bradford Book/ MIT Press.Google Scholar

Anderson, J. R (1993). Rules of the Mind. Hillsdale: NJ, Erlbaum.Google Scholar

Athanasiou, T. (1985). Artificial Intelligence: cleverly disguised politics. Compulsive Technology. T. Solomonides and L. Levidow. London, UK, Free Association Books: 13–35.Google Scholar

Axelrod, R. and , L. Tesfatsion (2007). A Guide for Newcomers to Agent-Based Modeling in the Social Sciences. Handbook of Computational Economics, Vol. 2: Agent-Based Computational Economics. K. L. Judd and L. Tesfatsion. Amsterdam, North-Holland, Available at http://www.econ.iastate.edu/tesfatsi/abmread.htm.Google Scholar

Bajscy, R. and , E. W. Large (1999). “When and Where Will AI Meet Robotics.” AI Magazine 20(3): 57–65.Google Scholar

Ballard, D. H. (1997). An Introduction to Natural Computation. Cambridge, MA., MIT Press.Google Scholar

Barad, K. (2003). “Posthumanist Performativity: Toward an Understanding of How Matter Comes to Matter.” Journal of Women in Culture and Society 28(3): 801–831.CrossRef Google Scholar

Baron-Cohen, S. (1995). Mindblindness. Cambridge, MA., MIT Press.Google Scholar

Bartlett, F. C. (1932). Remembering: A Study in Experimental and Social Psychology. New York, Macmillan.Google Scholar

Barwise, J. and , J. Etchemendy (1994). Hyperproof. New York, Cambridge University Press.Google Scholar

Bechtel, W. (1998). “Representations and Cognitive Explanations: Assessing the Dynamicist's Challenge in Cognitive Science.” Cognitive Science 22(3): 295–318.CrossRef Google Scholar

Bechtel, W. and , R. C. Richardson (1992). Discovering Complexity: Decomposition and localization as strategies in scientific research. Princeton, NJ., Princeton University Press.Google Scholar

Becker, H. (1982). The Art Worlds. Berkeley: CA, University of California Press.Google Scholar

Becker, H. S (forthcoming). What About Mozart? What About Murder? Accessed January 21, 2007 from: http://home.earthlink.net/∼hsbecker/mozart.htm.

Biagioli, M., Ed. (1999). Science Studies Reader. New York and London, Routledge.Google Scholar

Bijker, W. E., , T. E. Hughes, et al., Eds. (1997). The Social Construction of Technological Systems: new Directions in the Sociology and History of Technology. Cambridge, MA, The MIT Press.Google Scholar

Bloomfield, B. P. (1987). The Culture of Artificial Intelligence. The Question of Artificial Intelligence. B. Bloomfield. London, UK, Croom Helm: 59–105.Google Scholar

Bobrow, D. G. (1964). Natural Language Input for a Computer Problem-Solving System. Report TR-1, Project MAC, MIT, Cambridge, MA.Google Scholar

Boden, M. A. (1970). “Intentionality and Physical Systems.” Philosophy of Science 37: 200–214.CrossRef Google Scholar

Boden, M. A., Ed. (1990). The Creative Mind: Myths and Mechanisms. New York, Basic Books.Google Scholar

Boden, M. A (1994). Creativity and Computers. Artificial Intelligence and Creativity: An Interdisciplinary Approach. T. H. Dartnall. Dordrecht, Kluwer Academic Publishers.Google Scholar

Bolter, D. (1984). Turing's Man: Western Culture in the Computer Age. Chapel Hill, NC, University of North Carolina Press.Google Scholar

Born, R., Ed. (1987). Artificial Intelligence: The Case Against. London, Croom Helm.Google Scholar

Braitenberg, V. (1984). Vehicles: Experiments in Synthetic Psychology. Cambridge, MA., MIT Press.Google Scholar

Breazeal, C. and , B. Scassellati (2000). Challenges in Building Robots that Imitate People. Imitation in Animals and Artifacts. K. Dautenhahn and C. Nehaniv. Cambridge, MA, MIT Press.Google Scholar

Brick, T. and , M. Scheutz (2007). Incremental Natural Language Processing for HRI. HRI'07, Arlington, VA.CrossRef Google Scholar

Brooks, R., , C. Breazeal, et al. (1998). The Cog Project: Building a Humanoid Robot. Computation for Metaphors, Analogy and Agents. C. Nehaniv, Springer-Verlag. LNCS1562.Google Scholar

Brooks, R. A (1986). “A Robust Layered Control System for a Mobile Robot.” IEEE Transactions on Robotics and Automation 2(1): 14–23.CrossRef Google Scholar

Brooks, R. A (1991/1997). Intelligence without representation. Mind Design II. J. Haugeland. Cambridge, MA, The MIT Press. 395–420.

Brooks, R. A (1999). Cambrian Intelligence: The Early History of the New AI. Cambridge, MA., A Bradford Book/MIT Press.Google Scholar

Brooks, R. A (2002a). Flesh and Machines: How Robots Will Change Us. New York, Pantheon Books.Google Scholar

Brooks, R. A (2002b). “Lord of the Robots.” Technology Review 105(3): 78–83.Google Scholar

Brooks, R. A and , L. A. Stein (1994). “Building Brains for Bodies.” Autonomous Robots 1(1): 7–25.CrossRef Google Scholar

Bruce, B. (1999) Educational Reform: How Does Technology Affect Educational Change? Journal of Adolescent and Adult Education. Accessed Nov. 14, 2006 from: http://www.readingonline.org/electronic/jaal/9-99_Column.html.Google Scholar

Brucell, V., , M. Burton, et al. (1993). “Sex Discrimination: how do we tell the difference between male and female faces?” Perception 22: 131–152.CrossRef Google Scholar

Buchanan, B. G., Sutherland, G. L., et al. (1969). Heurstic DENDRAL: A program for generating explanatory hypothesis in organic chemistry. Machine Intelligence. B. Meltzer, Michie, D., and Swann, M. Edinburgh, Scotland, Edinburgh University Press. 4: 209–254.Google Scholar

Castañeda, C. and , L. Suchman (2005). Robots Visions. Accessed April 25, 2007 from:

http://www.comp.lancs.ac.uk/sociology/papers/***.pdf

Castells, M. (1996). The Rise of The Network Society. Malden: MA, Blackwell Publishers.Google Scholar

Castells, M. (2001). The Internet Galaxy: Reflections on the Internet, Business, and Society. Oxford: UK, Oxford University Press.CrossRef Google Scholar

Chalmers, D. J., R. M. French, et al. (1992). “High-level Perception, Representation, and Analogy.” Journal of Experimental and Theoretical Artificial Intelligence 4(3): 185–211.CrossRef Google Scholar

Chemero, A. (2000). “Anti-Representationalism and the Dynamical Stance.” Philosophy of Science 67: 626–647.CrossRef Google Scholar

Chomsky, N. (1957). Syntactic Structures. The Hague, Mouton.Google Scholar

Chrisley (2002). Artificial Intelligence. The Oxford Companion to the Mind. R. Gregory. Oxford, Oxford University Press.

Christiansen, M. H and , N. Chater (1999). “Connectionist Natural Language Processing: The State of the Art.” Cognitive Science 23(4): 417–437.CrossRef Google Scholar

Churchland (1997). On the Nature of Theories: A Neurocomputational Perspective. Mind Design II. J. Haugeland. Cambridge, MA, MIT Press: 251–292.

Churchland, P. M (1989). On the Nature of Theories: A Neurocomputatoinal Perspective. Mind Design II. J. Haugeland. Cambridge, MIT Press.Google Scholar

Clancey, W. J (1997). Situated Cognition: On Human Knowledge and Computer Representations. Cambridge, UK, Univeristy of Cambridge.Google Scholar

Clapin, H., Ed. (2002). Philosophy of Mental Representation. Oxford, Oxford University Press.Google Scholar

Clark, A. (1997). Being There: Putting Brain, Body, and World Together Again. Cambridge, MA, A Bradford Book/MIT Press.Google Scholar

Clark, A. (2001). Mindware. Cambridge, MA, MIT Press.Google Scholar

Clark, A. (2003). Natural-Born Cyborgs: Minds, Technologies, and the Future of Human Intelligence. Oxford, Oxford University Press.Google Scholar

Clark, E. V (1993). The Lexicon in Acquisition. Cambridge, UK, Cambridge University Press.CrossRef Google Scholar

Clynes, M. E and N. S. Kline (1960). “Cyborgs and Space.” Astronautics (Sept. 1960): 33–42.Google Scholar

Cohen, D. I. A. (1997). Theory of Computer Theory. New York, John Wiley and Sons.Google Scholar

Cohen, H. (1995). “The Further Exploits of AARON, Painter.” Stanford Humanities Review 4(2).Google Scholar

Cohen, P. R and , A. E. Howe (1988). “How Evaluation Guides AI Research.” AI Magazine Winter 1988: 35–43.Google Scholar

Collins, G. (1989). Coach. Inside Case-based Reasoning. C. Riesbeck and R. C. Schank. Hillsdale, NJ, Lawrence Erlbaum.Google Scholar

Collins, H. (1990). Artificial Experts: Social Knowledge and Intelligent Machines. Cambridge, MA, MIT Press.Google Scholar

Collins, H. (1992). “Hubert L. Dreyfus, Forms of Life, and a Simple Test for Machine Intelligence.” Social Studies of Science 22: 726–39.CrossRef Google Scholar

Collins, H. and , M. Kusch (1998). The Shape of Actions: What Humans and Machines Can Do. Cambridge, MA., MIT press.Google Scholar

Collins, H. and , T. Pinch (1998). The Golem: What everyone should know about science. Cambirdge, Cambridge University Press.Google Scholar

Cope, D. (1991). Computers and Musical Style. Madison: WI, A-R Editions, Inc.Google Scholar

Cope, D. (2001). Virtual Music: Computer Synthesis of Musical Style. Cambridge, MA., MIT Press.Google Scholar

Copeland, J. B (1997). “CYC: A case Study in Ontological Engineering.” Retrieved April 2003, from http://phil.indiana.edu/ejap/1997.Spring/copeland976.2.html.

Cottrell, G. W., C. Padgett, et al. (2000). Is all face processing holistic? The View from UCSD, ScientificCommons.

Crevier, D. (1993). The Tumultuous History of The Search for Artificial Intelligence. New York, NY, Basic Books.Google Scholar

Cussins, A. (1998). Nonconceptual Content of Experience and Conceptual Content of Thought. Unpublished manuscript.

Cussins, A. (in press). “Content, Embodiment and Objectivity – The Theory of Cognitive Trails.” Unpublished manuscript.

Dartnall, T., Ed. (2002). Creativity, Cognition, and Knowledge. Perspectives on Cognitive Science. Westport: CN, Praeger.Google Scholar

Davidson, A. (1990). Closing Up the Corpses. Meaning and Method. G. Boulos. Cambridge: MA, Harvard University Press.Google Scholar

Davis, M. (1988). Mathematical Logic and the Origin of Modern Computers. The Universal Turing Machine: A Half-Century Survey. R. Herken. Oxford, UK, Oxford University Press.Google Scholar

Day, R. (2005). “Clearing up “implicit knowledge”: Implications for Knowledge Management, information science, psychology, and social epistemology.” Journal of the American Society for Information Science and Technology 56(6): 630–635.CrossRef Google Scholar

Dell, G. S (1986). “A spreading-activation theory of retreival in sentence production.” Psychological Review 93: 283–321.CrossRef Google Scholar

Dell, G. S., , M. F. Schwartz, , N. Martin, , E. M Saffran, , D. A Gagnon (1997). “Lexical access in aphasic and nonaphasic speakers.” Psychological Review 104(801–939).CrossRef Google Scholar PubMed

Dell, G. S., F. Chang, Z. M. Griffin (1999). “Connectionist models of language production: Lexical access and grammatical encoding.” Cognitive Science 23: 517–542.CrossRef Google Scholar

Dell, G. S., C. Juliano, et al. (1993). “Structure and content in language production: A theory of frame constraints in phonological speech errors.” Cognitive Science 17: 149–195.CrossRef Google Scholar

DeLong, H. (1970). A Profile of Mathematical Logic. Reading, MA, Addison-Wesley.Google Scholar

Dennett, D. (1998). “Revolution, no! Reform.” Behavioral and Brain Sciences 21(5): 636–637.CrossRef Google Scholar

Dennett, D. C (1990). Cognitive Wheels: The Frame Problem of AI. The Philosophy of Artificial Intelligence. M. A. Boden. Oxford, UK, Oxford University Press: 147–170.Google Scholar

Dennett, D. C (1991). “Real Patterns.” Journal of Philosophy 88(1): 27–51.CrossRef Google Scholar

Dennett, D. C (1995). Darwin's Dangerous Idea. New York, Simon and Schuster.Google Scholar

Dennett, D. C (1997). True Believers: Intentional Strategy and Why It Works. Mind Design II. J. Haugeland. Cambridge, MA., MIT Press: 57–79.Google Scholar

Dennett, D. C (1977). Brainstorms. Cambridge, MA, MIT Press.Google Scholar

Descartes, R. (1979). Meditations on First Philosophy. Indianapolis, IN, Hackett Publishing Company.Google Scholar

Dewey, J. (1920/1948). Reconstruction of Philosophy. Boston, MA., Beacon Press.CrossRef

Dewey, J. (1938). Logic: The Theory of Inquiry. Carbondale, IL., Southern Illinois University Press.Google Scholar

Dewey, J. (1950). Common Sense and Science. Carbondale, IL, Southern Illinois University Press.Google Scholar

Dietrich, E. and , A. B. Markman (1998). “All information processing entails computation.” Behavioral and Brain Sciences 21(5): 637–38.CrossRef Google Scholar

Dretske, F. I (1994). If You Can't Make One, You Don't Know How It Works. Midwest Studies in Philosophy. P. French and T. Uehling. Notre Dame, IN., University of Notre Dame Press: 468–482.Google Scholar

Dreyfus, H. L (1972). What Computers Can't Do?New York, Harper Collins.Google Scholar

Dreyfus, H. L (1991). “Response to Collins, Artificial Experts.” Social Studies of Science 22: 717–726.CrossRef Google Scholar

Dreyfus, H. L (1992). What Computers Still Can't Do? A critique of Artificial Reason. Cambridge, MA, The MIT Press.Google Scholar

Dyer, F. C and , T. D. Seeley (1989). “On the evolution of the dance language.” The American Naturalist 133(4): 580–590.CrossRef Google Scholar

Edelman, G. M (1987). Neural Darwinism: The Theory of Neural Group Selection. New York, Basic Books.Google Scholar

Edwards, P. N (1996). The Closed World: Computers and The Politics of Discourse in Cold War America. Cambridge, MA, The MIT Press.Google Scholar

Ekbia, H. R (2001). Once Again, Artificial Intelligence at A Crossroads. Annual Meeting of the Society for Social Studies of Science, Boston, MA.Google Scholar

Ekbia, H. R (2002a). The Two Senses of “Common Sense.” 13th Midwest Artificial Intelligence and Cognitive Science Conference, Chicago, IL.Google Scholar

Ekbia, H. R (2002b). AI's Disparity Syndrome. Annual Meeting of the Society for Social Studies of Science, Milwaukee, WI.Google Scholar

Ekbia, H. R (2006). Taking Decisions into the Wild: An AI Perspective on the Design of iDSS. Intelligent Decision-Making Support Systems (I-DMSS): Foundations, Applications and Challenges J. Gupta, G. Forgionne and M. More. Berlin, Springer-Verlag.Google Scholar

Ekbia, H. R (forthcoming). “Informational Artifacts as Quasi-Objects.”

Ekbia, H. R and , L. Gasser (forthcoming). “Common Ground: For a Sociology of Code.”

Ekbia, H. R., , J Goldberg, , D Landy (2003). Starting Large or Small? An Unresolved Dilemma for Connectionist Models of Language Learning. Bootstrapping in Language Acquisition: Psychological, Linguistic and Computational Aspects. Bloomington, IN.Google Scholar

Ekbia, H. R and , N. Hara (2005). Incentive Structures in Knowledge Management. Encyclopedia of Knowledge Management. D. Schwartz. Hershey, PA, Idea Group.Google Scholar

Ekbia, H. R and , R. Kling (2003). Power in Knowledge Management in Late Modern Times. Academy of Management, Seattle, WA.Google Scholar

Ekbia, H. R and , A. Maguitman (2001). Context and Relevance: A Pragmatic Approach. 3rd International Conference on Modeling and Using Context, Dundee, UK, Springer Verlag.Google Scholar

Elman, J. L (1990). “Finding structure in time.” Cognitive Science 14: 179–211.CrossRef Google Scholar

Elman, J. L (1993). “Learning and development in neural networks: The importance of starting small.” Cognition 48: 71–99.CrossRef Google Scholar PubMed

Enfield, N. J and , S. C. Levinson (2006). Roots of Human Sociality: Culture, Cognition and Interaction. Oxford, Berg.Google Scholar

Epstein, J. M (2005). Remarks on the Foundations of Agent-Based Generative Social Science. The Brookings Institution: CSED Working Paper. Washington DC.Google Scholar

Falkenheiner, B., K. D. Forbus, et al. (1990). “The structure-mapping engine.” Artificial Intelligence 41(1): 1–63.CrossRef Google Scholar

Farah, M. J., K. D. Wiilson, et al. (1998). “What Is “Special” About Face Perception?” Psychological Review 105(3): 42–498.CrossRef Google Scholar PubMed

Fauconnier, G. (1994). Mental Spaces: Aspects of Meaning Construction in Natural Language. Cambridge, UK, Cambridge University Press.CrossRef Google Scholar

Feigenbaum, E. A and A. Barr, Eds. (1982). The Handbook of Artificial Intelligence. Reading, MA., Addison-Wesley.Google Scholar

Fikes, R. E., P. E. Hart, et al. (1972). “Learning and Executing Generalized Robot Plans.” Artificial Intelligence 3(4): 251–288.CrossRef Google Scholar

Fodor, J. and , Z. Pylyshyn (1997). Connectionism and Cognitive Architecture: A Critical Analysis. Mind Design II: Philosophy, Psychology, Artificial Intelligence. J. Haugeland. Cambridge, MA, The MIT Press: 309–350.Google Scholar

Fodor, J. A (1980). Methodological Solipsism Considered as a Research Strategy in Cognitive Psychology. Representations: Philosophical Essays on the Foundations of Cognitive Science, The Harvester Press.Google Scholar

Forbus, K. D., , D Gentner, et al. (1998). “Analogy just looks like high level perception: why a domain-general approach to analogical mapping is right” J. EXPT. THFOR. ARTIF. INTELL 10: 231–257.CrossRef Google Scholar

Forrest, S., Ed. (1991). Emergent Computation. Cambridge: MA, MIT Press.Google Scholar

Forsythe, D. E (2001). Studying Those Who Study Us: An Anthropologist in the World of Artificial Intelligence. Stanford, CA., Stanford University Press.Google Scholar

Foucault, M. (1977). Knowledge and Power: Selected Interviews and Other Writings. New York, Pantheon Books.Google Scholar

Foucault, M. (1994). The Order of Things: An Archaelogy of the Human Sciences. New York: NY, Random House/Vintage Books.Google Scholar

Foundalis, H. (2006). Phaeaco: A Cognitive Architecture Inspired by Bongard's Problems. Computer Science Dept. Bloomington, Indiana University.Google Scholar

Friedman, M. (1999). Reconsidering Logical Positivism. Cambridge, UK, Cambridge University Press.CrossRef Google Scholar

Funt, B. V (1980). “Problem-Solving with Diagrammatic Representations.” Artificial Intelligence 13.CrossRef Google Scholar

Gadamer, H.-G. (1976). Philosophical Hermeneutics. Berkeley, CA, University of California Press.Google Scholar

Gallistel, C. R (1998). Symbolic Processes in the Brain: The Case of Insect Navigation. An Invitation to Cognitive Science: Methods, Models, and Conceptual Issues. D. Scarborough and S. Sternberg. Cambridge, Mass., MIT Press/A Bradford Book.Google Scholar

Gasser, L. (1991). “Social conceptions of knowledge and action.” Artificial Intelligence 47(1): 107–138.CrossRef Google Scholar

Gasser, M. and , E. Colunga (2000). Babies, Variables, and Relational Correlations. 22nd Annual Conference of the Cognitive Science Society, Philadelphia, Lawrence Erlbaum.Google Scholar

Gazzaniga, M. S., , R Ivry, et al. (1998). Fundamentals of Cognitive Neuroscience. New York, W.W. Norton.Google Scholar

Gee, J. P (1999). An Introduction to Discourse Analysis. UK, Routledge.Google Scholar

Gell, A. (1998). Art and Agency: An Anthropological Theory. Oxford, Oxford University Press.Google Scholar

Genter, D. (1983). “Structure-Mapping: A Theoretical Framework for Analogy.” Cognitive Science 7(2): 155–170.CrossRef Google Scholar

Gerschenfeld, N. (1999). When Things Start to Think. New York, Henry Holt.Google Scholar

Gibson, J. J (1978). “The Ecological Approach to the Visual Perception of Pictures.” Leonardo 11(3): 227–235.CrossRef Google Scholar

Giere, R. N (1999). Science without Laws. Chicago, The University of Chicago Press.Google Scholar

Gieryn, T. F (1999). Cultural Boundaries of Science: Credibility on the line. Chicago: IL, Univeristy of Chicago Press.Google Scholar

Gilbert, N. (2004). Agent-Based Social Simulation. Center for Research on Social Simulation. Guilford: UK.Google Scholar

Gilbert, N. and , K. G. Troitzsch (2005). Simulation for the Social Scientist. Berkshire: UK, Open University Press.Google Scholar

Goodman, N. (1976). Languages of Art. Indianapolis, IN, Hacket Publishing Company.Google Scholar

Govindarajan, K. K., , S Grossberg, et al. (1994). A neural network model of auditory scene analysis and source segregation. Technical report. Boston, MA.Google Scholar

Graubard, S. R (1988). The Artificial Intelligence Debate: False Starts, Real Foundations. Cambridge, MA, MIT Press.Google Scholar

Greenberg, K., Ed. (2000). The Robot in the Garden. Cambridge: MA, MIT Press.Google Scholar

Grossberg, S. (1976). “Adaptive pattern classification and universal recoding: Part I. Parallel development and coding of neural feature detectors.” Biological Cybernetic 21: 121–134.CrossRef Google Scholar

Grossberg, S. (1987). “Competetive Learning: From Interactive Activation to Adaptive Resonance.” Cognitive Science 11(1): 23–63.CrossRef Google Scholar

Grossberg, S. (1995). “The Attentive Brain.” American Scientist 83: 438–449.Google Scholar

Grossberg, S. and , C. W. Myers (1999). The Resonant Dynamics of Conscious Speech. Technical Report. Boston, MA.Google Scholar

Grover, L. (1996). A Fast Quantum Mechanical Algorithm for Data base Search. 28th Annual ACM Symposium on the Theory of Computing.Google Scholar

Hacking, I. (1979). “What is logic?” The Journal of Philosophy LXXVI(6): 285–319.CrossRef Google Scholar

Hacking, I. (1983). Representing and Intervening: Introductory Topics in the Philosophy of Natural Science. Cambridge, Cambridge University Press.CrossRef Google Scholar

Hacking, I. (1999). Making Up People. Science Studies Reader. M. Biagioli. New York and London, Routledge: 161–171.Google Scholar

Hammond, K. J (1989). Case-Based Planning: Viewing Planning as a Memory Task. San Diego, CA., Academic Press.CrossRef Google Scholar

Hammond, K. J., T. M. Converse, et al. (1995). “The Stabilization of Environments.” Artificial Intelligence 72(1–2): 305–327.CrossRef Google Scholar

Haraway, D. (1991). Simians, Cyborgs, and Women: The Reinvention of Nature. New York, Routledge.Google Scholar

Haraway, D. (1997). Modest_Witness@Second_Millenium.FemaleMan_Meets_OncoMouseTM. New York, Routledge.Google Scholar

Haraway, D. (2003). The Companion Species Manifesto: Dogs, People and Significant Others. Chicago, Prickly Paradigm Press.Google Scholar

Haraway, D. J (1989). Primate Visions: Gender, Race, and Nature in the World of Modern Science. New York and London, Routledge.Google Scholar

Harnad, S. (1990). “The symbol grounding problem.” Physica D 42: 335–346.CrossRef Google Scholar

Haugeland, J. (1978/98). The Plausibility of Cognitivism. Having Thought. J. Haugeland. Cambridge, MA., Harvard University Press.

Haugeland, J., Ed. (1981). Mind Design I. Cambridge, MA, A Bradford Book/MIT Press.Google Scholar

Haugeland, J. (1985). Artificial Intelligence: The Very Idea. Cambridge, MA, Bradford/MIT Press.Google Scholar

Haugeland, J., Ed. (1997). Mind Design II: Philosophy, Psychology, Artificial Intelligence. Cambridge, Mass., A Bradford Book/MIT Press.Google Scholar

Haugeland, J. (1998). Having Thought: Essays in the Metaphysics of Mind. Cambridge, Mass., Harvard University Press.Google Scholar

Hayes, P. J (1973). Computation and Deduction. 2nd Mathematical Fooundations of Computer Science Symposium, Czechoslovakian Academy of Sciences.Google Scholar

Hayes, P. J (1990). The Naive Physics Manifesto. The Philosophy of Artificial Intelligence. M. A. Boden. Oxford, UK, Oxford University Press: 171–205.Google Scholar

Hayles, N. K (1999). How we became posthuman: Virtual bodies in cybernetics, literature, and informatics. Chicago, Chicago University Press.CrossRef Google Scholar

Hayles, N. K (2005). “Computing the Human.” Theory, Culture & Society 22(1): 131–151.CrossRef Google Scholar

Hebb, D. (1949). Organization of Behavior. New York, Wiley.Google Scholar

Hempel, C. G and , P. Oppenheim (1948). “Studies in the Logic of Explanation.” Philosophy of Science 15: 135–175.CrossRef Google Scholar

Hempel, C. G and , P. Oppenheim (1949). Studies in the Logic of Explanation. Aspects of Scientific Explanation. C. G. Hempel. New York, Macmillan.Google Scholar

Hennessy, J. L and , D. A. Patterson (1996). Computer Architecture: A Quantitative Approach. San Francisco, CA., Morgan Kaufmann Publishers.Google Scholar

Hertz, J., , A Krogh, et al. (1991). Introduction to the Theory of Neural Computation. Redwood City, CA, Addison-Wesley.Google Scholar

Hinton, G. and , T. Sejnowski (1986). Learning and relearning in Boltzmann machines. Parallel Distributed Processing. D. Rumelhart and J. McClelland. Cambridge, MA, MIT Press. 1: 282–317.Google Scholar

Hirsh-Pasek, K. and , R. M. Golinkoff (1996). The Origins of Grammar: Evidence from Early Language Comprehension. Cambridge, MA., MIT Press.Google Scholar

Hofstadter, D. R (1979). Gödel, Escher, Bach: an Eternal Golden Braid. New York, N.Y., Basic Books.Google Scholar

Hofstadter, D. R (1985). Metamagical Themas: Questing for the Essence of Mind and Pattern. New York, N.Y., Basic Books.Google Scholar

Hofstadter, D. R (1985b). Waking Up from the Boolean Dream, Or, Subcognition as Computation. Metamagical Themas: Questing for the Essence of Mind and Pattern. New York, Basic Books.Google Scholar

Hofstadter, D. R (1995). Fluid Concepts and Creative Analogies. New York, N.Y., Basic Books.Google Scholar

Hofstadter, D. R (1997). Le Ton beau de Marot: In Praise of the Music of Language. New York, Basic Books.Google Scholar

Hofstadter, D. R (1999). Moore's Law, Artificial Evolution, and the Fate of Humanity. Festschrift in Honor of John Holland's 70th Birthday. M. Mitchell.Google Scholar

Hofstadter, D. R (2001). Analogy as the Core of Cognition. Integration of Theory and Data from the Cognitive, Computational, and Neural Sciences. K. J. Holyoak, Gentner, D., and Kokinov, B. Cambridge, MA., MIT Press.Google Scholar

Hofstadter, D. R (2002). Staring Emmy Straight in the Eye – and Doing My Best Not to Flinch. Creativity, Cognition, and Knowledge. T. Dartnall. Westport: CN, Praeger: 67–100.Google Scholar

Hofstadter, D. R and , D. C. Dennett (1982). The Mind's I: Fantasies and Reflections on Self and Soul. New York, Basic Books.Google Scholar

Hofstadter, D. R and , D. Moser (1989). “To Err is Human: To Study Error-Making in Cognitive Science.” Michigan Quarterly Review 28(2): 185–215.Google Scholar

Holland, J. (1975). Adaptation in Natural and Artificial Systems. Ann Arbor, Michigan, University of Michigan Press.Google Scholar

Holland, J. (1995). Hidden Order: How Adaptation Builds Complexity. Reading, MA., Addison-Wesley.Google Scholar

Holland, J. H (1986). Escaping Brittleness: The Possibilities of General-purpose Learning Algorithms Applied to Parallel Rule-based Systems. Machine Learning: An Artificial Intelligence Approach. R. S. Michalski, J. G. Carbonell and T. M. Mitchell. Los Altos, CA., Morgan Kaufmann. II: 593–623.Google Scholar

Hölldobler, B. and , E. O. Wilson (1990). Ants. Cambridge, MA, Belknap Press of Harvard University Press.CrossRef Google Scholar

Holyoak, K. J and , P. Thagard (1995). Mental Leaps: Analogy in Creative Thought. Cambridge: MA, MIT Press/Bradford Books.Google Scholar

Hopfield, J. (1982). Neural Networks and Physical Systems with Emergent Collective Computational Abilities. National Academy of Sciences, USA79.Google Scholar PubMed

Hume, D. (1739). A Treatise of Human Nature. London, Penguin Books.Google Scholar

Hummel, J. E and , K. J. Holyoak (1997). “Distributed Representations of Structure: A Theory of analogical access and mapping.” Psychological Review 104: 427–466.CrossRef Google Scholar

Hurlbert, A. and , T. Poggio (1988). “Making machines (and artificial intelligence).” Daedalus 117(1): 213–239.Google Scholar

Huskey, V. R and , H. D. Huskey (1980). “Lady Lovelace and Charles Babbage.” Annals of History of Computing 2: 299–329.CrossRef Google Scholar

Hutchins, E. (1995). Cognition in The Wild. Cambridge, Mass., MIT Press.Google Scholar

James, W. (1907/1998). Pragmatism and The Meaning of Truth. Cambridge, MA., Harvard University Press.

Johnson-Laird, P. (1988). The Computer and the Mind: An Introduction to Cognitive Science. Cambridge, MA, Harvard University Press.Google Scholar

Jordan, M. I (1986). Attractor Dynamics and Parallelism in a Connectionist Sequential Machine. 8th Annual Conference of Cognitive Science Society, Hillsdale, NJ, Lawrence Erlbaum.Google Scholar

Joy, B. (2000). “Why the future doesn't need us?” Wired 8(4).Google Scholar

Joyce, J. (1996). When/why/of what is less more? Center for Cogntive Science. Edinburgh, University of Edinburgh. M.Sc. Dissertation.Google Scholar

Kail, R. (1984). The development of memory. New York, W. H. Freeman.Google Scholar

Kaipainen, M. and , R. F. Port (unpublished). Speech Cycling.

Kanerva, P. (1988). Sparse Distributed Memory. Cambridge, MA., MIT Press.Google Scholar

Karmiloff-Smith, A. (1992). Beyond modularity: a developmental perspcetive on cognitive science. Cambridge: MA, MIT Press/Bradford Books.Google Scholar

Keller, E. F (2007). Booting up baby. Genesis Redux Essays in the History and Philosophy of Artificial Life. J. Riskin. Chicago, University of Chicago Press: 334–345.Google Scholar

Kelso, J. A. S. (1995). Dynamic Patterns: The Self-Organization of Brain and Behavior. Cambridge, MA., MIT Press.Google Scholar

Kennedy, J. and , R. C. Eberhart (2001). Swarm Intelligence. New York, Morgan Kaufmann.Google Scholar

Kintsch, W. (2000). “Metaphor comprehension: A computational theory.” Psyhonomic Bulletin and Review 7: 257–266.CrossRef Google Scholar PubMed

Kirsh, D. (1991). “Today the earwig, tomorrow man?” Artificial Intelligence 47: 161–184.CrossRef Google Scholar

Kling, R. (1980). “Social analyses of computing: Theoretical perspectives in recent empirical research.” Computing Surveys 12(1): 61–110.CrossRef Google Scholar

Kling, R. (1997). Hopes and Horrors: Technological Utopianism and Anti-Utopianism in Narratives of Computerization. Computerization and Controversy: Value Conflicts and Social Choices. R. Kling. San Diego, CA, Academic Press: 40–58.Google Scholar

Kling, R. (1999). What is Social Informatics and Why Does it Matter? D-Lib Magazine. 5.

Kling, R. and , S. Iacono (1995). Computerization movements and the mobilization of support for computerization. Ecologies of knowledge. L. S. Star. New York, SUNY: 119–153.Google Scholar

Knuth, D. (1983). The Art of Computer Programming. Reading, MA., Addison-Wesley.Google Scholar

Koestler, A. (1964). The Act of Creation. New York: NY, Macmillan.Google Scholar

Kohler, R. (1999). Moral Economy, Material Culture, and Community in Drosophilia Genetics. The Science Studies Reader. M. Biagioli. New York and London, Routledge: 243–257.Google Scholar

Kolodner, J. L (1996). Making the Implicit Explicit: Clarifying the Principles of Case-Based Reasoning. Case-Based Reasoning: Experiences, Lessons, and Future Directions. D. B. Leake. Menlo Park, CA., AAAI Press/MIT Press: 349–370.Google Scholar

Kolodner, J. L and , D. Leake (1996). A Tutorial Introduction to Case-Based Reasoning Case-Based Reasoning: Experiences, Lessons and Future Directions. D. Leake. Cambridge, MA, MIT Press: 31–65.Google Scholar

Kowalski, R. A (1977). Algorithm=Logic+Control. Memorandum, Imperial College. London, UK.Google Scholar

Kuhn, T. (1962). The Structure of Scientific Revolutions. Chicago, University of Chicago Press.Google Scholar

Kurzweil, R. (1999). The Age of Spiritual Machines: When Computers Exceed Human Intelligence. New York, N.Y., Viking.Google Scholar

Laham, D. (1997). Latent Semantic Analysis approaches to categorization. 19th annual meeting of the Cognitive Science Society, Erlbaum.Google Scholar

Lakoff, G. (1987). Women, Fire and Dangerous Things. Chicago, University of Chicago Press.CrossRef Google Scholar

Landauer, T. K., Foltz, P. W., & Laham, D. (1998). “Introduction to Latent Semantic Analysis.” Discourse Processes 25: 259–284.CrossRef Google Scholar

Landauer, T. K., Laham, D., & Foltz, P. W. (1998). “Learning human-like knowledge by Singular Value Decomposition: A progress report. In M. I. Jordan, M. J. Kearns & S. A. Solla (Eds.), Advances.”

Landauer, T. K and , S. T. Dumais (1997). “A solution to Plato's problem: the latent semantic analysis theory of acquisition, induction, and representation of knowledge.” Psychological Review 104: 211–240.CrossRef Google Scholar

Landauer, T. K., , D Laham, et al. (1997). How well can passage meaning be derived without using word order? A comparison of Latent Semantic Analysis and humans. 19th annual meeting of the Cognitive Science Society, Erlbaum.Google Scholar

Landes, D. (2000). Revolution in Time: Clocks and the Making of the Modern World. London, Viking Press.Google Scholar

Langton, C. G (1989). Artificial Life. Redwood City, CA., Addison-Wesley.Google Scholar

Lanier, J. (2000) One Half of A Manifesto: Why stupid software will save the future from neo-Darwinian machines. Wired: 8(12).Google Scholar

Larkin, J. and , H. A. Simon (1987). “Why a Diagram is (Sometimes) Worth Ten Thousand Words.” Cognitive Science 11(1): 65–100.CrossRef Google Scholar

Latash, M. L (1993). Control of Human Movement. Champaign, IL., Human Kinetics: 1–48.Google Scholar

Latour, B. (1987). Science in Action. Cambridge, MA., Harvard University Press.Google Scholar

Latour, B. (1993). We Have Never Been Modern. Cambridge: MA, Harvard University Press.Google Scholar

Latour, B. (1999). Pandora's Hope: Essays on the Reality of Science Studies. Cambridge, MA., Harvard University Press.Google Scholar

Latour, B. (2005). Reassembling the Social: An Introduction to Actor-Network Theory. Oxford, Oxford University Press.Google Scholar

Leake, D. B., Ed. (1996). Case-Based Reasoning: Experiences, Lessons, and Future Directions. Menlo Park, CA., AAAI Press/MIT Press.Google Scholar

Leclerc, J. and , F. Gosselin (2004). Processes of artistic creativity: The case of Isabelle Hayeur. Twenty-Seventh Conference of the Cognitive Science Society, Mahwah: NJ, Erlbaum.Google Scholar

Leclerc, J. and , F. Gosselin (2005). ACE: A Model of the Cognitive Strategies of a Contemporary Artist. Twenty-Seventh Conference of the Cognitive Science Society, Mahwah: NJ, Erlbaum.Google Scholar

Lenat, D. B (1997a). From 2001 to 2001: Common Sense and the Mind of HAL. Hal's Legacy: 2001's Computer As Dream & Reality. D. G. Stork. Cambridge, Mass., MIT Press.Google Scholar

Lenat, D. B (1997b). “The Dimensions of Context Space.” Retrieved April, 2003, from www.cyc.com.

Lenat, D. B (2002). Cyc Workshop. Presentation.Google Scholar

Lenat, D. B and , E. A. Feigenbaum (1991). “On the Thresholds of Knowledge.” Artificial Intelligence 47(1–3): 185–250.CrossRef Google Scholar

Lenat, D. B and , R. V. Guha (1990). Building Large Knowledge-Based Systems. Reading, Mass., Addison Wesley.Google Scholar

Lenat, D. B., , M Prakash, et al. (1986). “Using common-sense knowledge to overcome brittleness and knowledge acquisition bottlenecks.” AI Magazine 7: 65–85.Google Scholar

Levelt, W. J. M. (1989). Speaking: From intention to articulation. Cambridge, MA., MIT Press.Google Scholar

Lewis, D. (1971). “Analog and Digital.” Nous 5(3): 321–327.CrossRef Google Scholar

Lewontin, R. C (1998). The Evolution of Cognition: Questions We Will Never Answer. An Invitation to Cognitive Science: Methods, Models, and Conceptual Issues. D. Scarborough and S. Sternberg. Cambridge, MA., A Bradford Book/MIT Press. 4: 107–132.Google Scholar

Lloyd, E. A (1994). The Structure and Confirmation of Evolutionary Theory. Princeton, N.J., Princeton University Press.Google Scholar

Llyod, G. (1999). Science in Antiquity: The Greek and Chinese Cases and Their Relevance to the Problems of Culture and Cognition. Science Studies Reader. M. Biagioli. New York and London, Routledge: 302–316.Google Scholar

Loy, G. (1989). Composing with Computers: A Survey of Some Compositional Formalisms and Music Programming Languages. Current Directions in Computer Music Research. M. Mathews and J. R. Pierce. Cambridge: MA, MIT Press.Google Scholar

Mackay, W. A., D. J. Crammond, et al. (1986). “Measurements of human forearm viscoelasticity.” Journal of Biomechanics 19: 231–238.CrossRef Google Scholar PubMed

Manna, Z. and , R. Waldinger (1985). The Logical Basis for Computer Programming. Reading, Mass., Addison-Wesley.Google Scholar

Maris, M. and , R. T. Boekhorst (1996). Exploiting physical constraints: Heap formation through behavioral error in a group of robots. IEEE/RSJ International Conference on Intelligent Robots and Systems.Google Scholar

Marr, D. (1982). Vision. San Francisco, CA, Freeman.Google Scholar

Marshall, J. and , D. R. Hofstatder (1997). “The Metacat Project: a self-watching model of analogy-making.” Cognitive Studies: The Bulletin of Japanese Cogn.Sci.Soc. 4(4).Google Scholar

Marshall, J. B (1999). Metacat: A Self-Watching Cognitive Architecture for Analogy-Making and High-Level Perception. Computer Science Dept. Bloomington, Indiana University.Google Scholar

Mataric, M. J (1992). “Intergation of reprenstation into goal-driven behavior-based robots.” IEEE Transactions on Robotics and Automation 8(3): 304–312.CrossRef Google Scholar

Mazlish, B. (1993). The Fourth Discontinuity: the co-evolution of humans and machines. New Haven, Yale University Press.Google Scholar

McCarthy, J. (1980). “Circumscription – A Form of Non-Monotonic Reasoning.” Artificial Intelligence 13: 27–39.CrossRef Google Scholar

McCarthy, J. (1986). “Applications of Circumscription to Formalizing Commonsense Knowledge.” Artificial Intelligence 28(1): 89–116.CrossRef Google Scholar

McCarthy, J. and , P. J. Hayes (1969). Some Philosophical Problems from the Standpoint of Artificial Intelligence. Machine Intelligence. B. M. D. Michie. Edinburgh, UK, Edinburgh University Press. 4.Google Scholar

McClelland, J. and , D. Rumelhart (1986). Parallel Distributed Processing. Cambridge, MA, MIT Press.Google Scholar

McCorduck, P. (1979). Machines who think. San Francisco, CA, W. H. Freeman.Google Scholar

McCorduck, P. (1991). Aaron's Code: meta-art, artificial intelligence and the work of Harold Cohen. New York, Freeman.Google Scholar

McCulloch, W. S and , W. H. Pitts (1943). “A Logical Calculus of the Ideas Immanent in Nervous Activity.” Bulletin of Mathematical Biophysics 5: 115–133.CrossRef Google Scholar

McDermott, D. (1976). “Artificial intelligence meets natural stupidity.” SIGART Newsletter 57: 4–9.CrossRef Google Scholar

McDermott, D. (1982). “A Temporal Logic for Reasoning about Processes and Plans.” Cognitive Science 6: 101–155.CrossRef Google Scholar

McDermott, D. (1987). “A Critique of Pure Reason.” Computational Intelligence 3(1): 151–160.CrossRef Google Scholar

McDonough, R. (2002). Emergence and Creativity. Creativity, Cognition, and Knowledge. T. Dartnall. Westport: CN, Praeger: 282–301.Google Scholar

McGraw, G. and , D. R. Hofstadter (2002). Letter Spirit: Perception and Creation of Diverse Alphabetic Styles. Creativity, Cognition, and Knowledge. T. Dartnall. Westport: CN, Praeger: 251–266.Google Scholar

McLeod, P., , K Plunkett, et al. (1998). Introduction to Connectionist Modelling of Cognitive Processes. New York, Oxford Univeristy Press.Google Scholar

McNeal, C. (1998). The Medieval Art of Love. New York, N.Y., Gaimann & King Ltd.Google Scholar

Mead, G. H (1934). Mind, Self, and Society from the Standpoint of a Social Behaviorist. Chicago, Chicago Univeristy Press.Google Scholar

Meglicki, Z. (2000). “Introduction to Quantum Computing.” Retrieved May 1, 2003, from http://www.ovpit.indiana.edu/B679.

Menzel, P. and F. D'Aluisio (2000). Robo sapiens. Cambridge: MA, MIT Press.Google Scholar

Minsky, M. (1975). A framework for representing knowledge. The Psychology of Computer Vision. P. H. Winston. New York, McGraw-Hill: 211–277.Google Scholar

Minsky, M. (1985). The Society of Mind. Cambridge, MA., MIT Press.Google Scholar

Minsky, M. (1995). “Future of AI Technology.” Toshiba Review 47(7).Google Scholar

Minsky, M. (2005). The Emotion Machine. Accessed November 28, 2006 from: web.media.mit.edu/∼minsky/.

Mitchell, M. (1993). Analogy-Making as Perception: A Computer Model. Cambridge, MA, MIT Press.Google Scholar

Mitchell, M. (1996). An Introduction to Genetic Algorithms. Cambridge, MA., MIT Press.Google Scholar

Mitchell, M. (1998). “Theories of structure versus theories of change.” Behavioral and Brain Sciences 21(5): 645–46.CrossRef Google Scholar

Moravec, H. (1998). Mind Children: The Future of Robot and Human Intelligence. Cambridge and New York, Cambirdge University Press.Google Scholar

Morris, W. C., G. W. Cottrell, et al. (1999). “A Connectionist Simulation of the Empirircal Acquisition of Grammatical Relations.” Cognitive Science.Google Scholar

Mortensen, C. (1989). Mental Images: Should Cognitive Science Learn From Neurophysiology. Computers, Brains, and Minds: Essays in Cognitive Scienc. P. Slezak and W. R. Albury. Dodrecht, Kluwer Academic Publishers.Google Scholar

Nagel, T. (1974). “What is it like to be a bat?” Philosophical Review 4: 435–450.CrossRef Google Scholar

Neumaier, O. (1987). A Wittgensteinian View of Artificial Intelligence. Aritificial Intelligence: The Case Against. R. Born. London, Croom Helm: 132–174.Google Scholar

Newborn, M. (1997). Kasparov versus Deep Blue: Computer Chess Comes of Age. New York, N.Y., Springer.CrossRef Google Scholar

Newell, A. (1990). Unified Theories of Cognition. Cambridge, MA., Harvard University Press.Google Scholar

Newell, A., J. C. Shaw, et al. (1960). Report on a General Problem-Solving Program. Proceedings of the International Conference on Information Processing, Paris.Google Scholar

Newell, A. and , H. A. Simon (1961). GPS, a program that simulates human thought. Lernende Automaten. H. Billing. Munich, Oldenbourg: 109–124.Google Scholar

Newell, A. and , H. A. Simon (1976). “Computer Science as Empirical Inquiry.” Communications of the ACM 19(3): 113–126.CrossRef Google Scholar

Newport, E. L (1990). “Maturational constraints on language learning.” Cognitive Science 14: 11–28.CrossRef Google Scholar

Noble, D. F (1977). America by Design: Science, Technology, and the Rise of Corporate capitalism. Oxford, UK, Oxford University Press.Google Scholar

Noble, D. F (1984). Forces of Production: A Social History of Industrial Automation. New York, NY, Alfred A. Knopf.Google Scholar

Norton, A. (1995). Dynamics: An Introduction. Mind as Motion. R. F. Port and T. v. Gelder. Cambridge, MA., MIT Press: 45–68.Google Scholar

Oyama, S. (2000). Evolution's Eye: A Systems View of the Biology-Culture Divide. Durham, NC, Duke University Press.CrossRef Google Scholar

Peirce, C. S (1905/1940). Critical Common-Sensism. The Philosophy of Peirce: Selected Writings. J. Buchler. New York: Harcourt, Brace & Company: 290–301.

Petitot, J., F. J. Varela, et al. (1999). Naturalizing Phenomenology: Issues in Contemporary Phenomenology and Cogntive Science. Stanford, CA., Stanford University Press.Google Scholar

Petroski, H. (1989). The Pencil: A History of Design and Circumstances. New York, Knopf.Google Scholar

Pfeifer, R. and , C. Scheier (1999). Understanding Intelligence. Cambridge, MA., MIT Press.Google Scholar

Piaget, J. (1952). The Origins of Intelligence in Children. New York, International University Press.CrossRef Google Scholar

Pinker, S. (1984). Language Learnability and Language Development. Cambridge, MA., Harvard University Press.Google Scholar

Pinker, S. (1991). “Rules of Language.” Science 253: 530–535.CrossRef Google Scholar PubMed

Pinker, S. and , A. Prince (1988). “On Language and Connectionism: Analysis of a parallel distributed processing model of language acquisition.” Cognition 28: 73–193.CrossRef Google Scholar PubMed

Plate, T. (1995). Holographic Reduced Representations. Department of Computer Science. Toronto, University of Toronto.Google Scholar

Plunkett, K. and , P. Juola (1999). “A Connectionist Model of English Past Tense and Plural Morphology.” Cognitive Science 23(4): 463–490.CrossRef Google Scholar

Plunkett, K. and , V. Marchman (1991). “U-shaped learning and frequency effects in a multi-layered perceptron: Implications for child language acquisition.” Cognition 38: 43–102.CrossRef Google Scholar

Poincaré, H. (1952). Science and Hypothesis. New York, Dover Publications.Google Scholar

Poincaré, H. (1982). The Foundations of Science: Science and hypothesis, the value of science, science and method. Washington, DC, University Press of America.Google Scholar

Polanyi, M. (1958). Personal Knowledge: Towards a Postcritical Philosophy. Chicago, Chicago University Press.Google Scholar

Popper, K. R (1972). Two Faces of Common Sense. Objective Knowledge: An Evolutionary Approach. Oxford, UK, Clarendon Press.Google Scholar

Port, R. F and T. van Gelder (1995). Mind as Motion: Explorations in the Dynamics of Cognition. Cambridge, MA., A Bradford Book/MIT Press.Google Scholar

Pratt, V. (1994). “Visit to Cyc.” Retrieved Accessed July 24, 2002, from http://boole.stanford.edu/pratt.html.

Preskill, J. (1997). “Lecture Notes for Physics 229: Quantum Information and Computation.” Retrieved Accessed May 4 2000, from www.theory.caltech.edu/people/preskill/ph229.

Prinz, J. J and , L. W. Barsalou (2002). Acquisition and Productivity in Perceptual Symbol Systems: An Account of Mundane Creativity. Creativity, Cognition, and Knowledge. T. Dartnall. Westport: CN, Praeger: 105–126.Google Scholar

Pulvermüller, F. (1999). “Words in the Brain's Language.” Behavioral and Brain Sciences 22: 253–279.CrossRef Google Scholar

Putnam, H. (1975). Philosophical Papers: Mind, Language and Reality. Cambridge, UK, Cambridge University Press.CrossRef Google Scholar

Putnam, H. (1990). Realism with a Human Face. Cambridge, MA., Harvard University Press.Google Scholar

Pylyshyn, Z. W (1984). Computation and Cognition: Toward a Foundation for Cognitive Science. Cambridge, MA, Bradford/MIT Press.Google Scholar

Quartz, S. R and , T. J. Sejnowski (1997). “The Neural Basis of Cognitive Development: A Constructivist Manifesto.” Brain and Behavioral Sciences 20: 537–596.CrossRef Google Scholar PubMed

Quine, W. V and , J. S. Ullian (1978). The Web of Belief. New York, McGraw-Hill.Google Scholar

Reeke, G. N and , G. M. Edelman (1988). “Real brains and artificial intelligence.” Daedalus 117(1): 143–173.Google Scholar

Regier, T. and , L. Carlson (2001). “Grounding spatial language in perception: An empirical and computational investigation.” Journal of Experimental Psychology: General 130: 273–298.CrossRef Google Scholar PubMed

Rehling, J. (2002). Results in Letter Spirit Project. Creativity, Cognition, and Knowledge. T. Dartnall. Westport: CN, Praeger: 272–278.Google Scholar

Reid, T. (1785/1969). Essays on the Intellectual Powers of Man. Cambridge, MA., The MIT Press.

Restivo, S. (2001). Bringing Up and Booting Up: Social Theory and the Emergence of Socially Intelligent Robots. IEEE Conference on Robotics and Cybernetics, IEEE.Google Scholar

Rhode, D. L. T. and , D. C. Plaut (1999). “Language acquisition in the absence of explicit negative evidence: how important is starting small?” Cognition 72: 67–109.CrossRef Google Scholar

Riesbeck, C. and , R. C. Schank (1989). Inside Case-based Reasoning. Hillsdale, N.J., Lawrence Erlbaum.Google Scholar

Riesbeck, C. K (1996). What Next? The Future of Case-Based Reasoning in Post-Modern AI. Case-Based Reasoning: Experiences, Lessons, and Future. D. B. Leake. Menlo park, CA., AAAI Press/MIT Press: 371–388.Google Scholar

Risan, L. (1997). Artificial Life: A technoscience leaving modernity? An Anthropology of subjects and objects. Accessed April 19, 2003 from: http://anthrobase.com/Txt/R/Risan_L_05.htm.

Riskin, J. (2007). Genesis Redux: Essays in the History and Philosophy of Artificial Life. Chicago, University of Chicago Press.CrossRef Google Scholar

Roberts, S. and , H. Pashler (2000). “How persuasive is a good fit? A comment on theory testing.” Psychological Review 107: 358–367.CrossRef Google Scholar

Rochester, N., , J Holland, et al. (1956). “Test on a cell assembly theory of the action of the brain, using a large digital computer.” IRE Transactions on Information Theory IT-2: 80–93.CrossRef Google Scholar

Rosenblatt, P. (1958). “The Perceptron: A probabilistic model for information storage and organization in the brain.” Psychological Review 65: 386–408.CrossRef Google Scholar

Roszak, T. (1994). The Cult of Information: A Neo-Luddite Treatise on High-Tech, Artificial Intelligence, and The True Art of Thinking. Berkeley, CA, University of California Press.Google Scholar

Rouse, J. (1987). Knowledge and Power: Toward a Political Philosophy of Science. Ithaca: N.Y., Cornell University Press.Google Scholar

Rouse, J. (1999). Understanding Scientific Practices: Cultural Studies of Science as a Philosophical Program. The Science Studies Reader. M. Biagioli. New York and London, Routledge: 442–456.Google Scholar

Rumelhart, D. E (1989). The Architecture of Mind: A Connectionist Approach. Mind Design II: Philosophy, Psychology, Artificial Intelligence. J. Haugeland. Cambridge, MA., MIT Press: 205–232.Google Scholar

Rumelhart, D. E (1997). The Architecture of Mind: A Connectionist Approach. Mind Design II. J. Haugeland. Cambridge, MA, MIT Press: 205–232.Google Scholar

Rumelhart, D. E., G. E. Hinton, et al. (1986). Learning internal representations by error propagation. Parallel Distributed Processing. D. E. R. a. J. L. McClelland. Cambridge, MA., MIT Press. 2.Google Scholar

Rumelhart, D. E and , D. Norman (1982). “Simulating a Skilled Typist: A Study of Skilled Cognitive–Motor Performance.” Cognitive Science 6(1): 1–36.CrossRef Google Scholar

Rumelhart, D. E and , D. Zipser (1985). “Feature discovery by competitive learning.” Cognitive Science 9: 75–112.CrossRef Google Scholar

Russell, S. J and , P. Norvig (1995). Artificial Intelligence: A Modern Approach, Prentice Hall.Google Scholar

Saffran, J. R., R. N. Aslin, et al. (1996). “Statistical learning by 8-month old infants.” Science 274(5294): 1926–1928.CrossRef Google Scholar PubMed

Santambrogio, M. and , P. Violi (1988). Introduction. Meaning and Mental Representation. M. Santambrogio, P. Violi and U. Eco. Bloomington, IN, Indiana University Press: 3–23.Google Scholar

Scassellati, B. (1998). Imitation and Mechanisms of Joint Attention: A Developmental Structure for Building Social Skills on a Humanoid Robot. Computation for Metaphors, Analogy and Agents. C. Nehaniv, Springer-Verlag. 1562.Google Scholar

Scassellati, B. (1999). A Binocular, Foveated Active Vision System, MIT, Artificial Intelligence Laboratory.

Scassellati, B. (2000). Investigating Models of Social Development Using a Humanoid Robot. Biorobotics. B. Webb and T. Consi. Cambridge, MA, MIT Press.Google Scholar

Schaffer, S. (1994) Babbage's Intelligence: Calculating Engines and the Factory System. Accessed April 14, 2004 from: http://www.wmin.ac.uk/mad/schaffer/schaffer01.html.

Schank, R. C (1972). “Conceptual Dependency: A theory of natural language understanding.” Cognitive Psychology 3(4): 552–631.CrossRef Google Scholar

Schank, R. C (1982). Dynamic Memory: A Theory of Learning in Computers and People. Cambridge, UK, Cambridge University Press.Google Scholar

Schank, R. C (1986). Explanation Patterns. Hillsdale, N.J., Lawrence Erlbaum Assoc.Google Scholar

Schank, R. C (1995). Information Is Surprises. The Third Culture: Beyond the Scientific Revolution. J. Brockman. New York, Simon and Schuster.Google Scholar

Schank, R. C and , R. P. Abelson (1977). Scripts, Plans, Goals, and Understanding. Hillsdale, NJ, Lawrence Erlbaum Assoc.Google Scholar

Schank, R. C and , L. Birnbaum (1984). Memory, Meaning, and Syntax. Talking Minds: The Study of Language in Cognitive Science. Cambridge, MA., MIT Press: 209–251.Google Scholar

Schank, R. C and , A. Kass (1988). Knowledge Representation in People and Machines. Meaning and Mental Representations. U. Eco, M. Santambrogio and P. Violi. Bloomington and Indianapolis, Indiana University Press: 181–200.Google Scholar

Schank, R. C., , A Kass, et al. (1994). Inside Case-based Explanation. Hillsdale, N.J., Lawrence Erlbaum Assoc.Google Scholar

Schank, R. C and , D. B. Leake (2001). Natural Language Processing: Models of Roger Schank and His Students. Encycopedia of Cognitive Science.Google Scholar

Schank, R. C and , C. Riesbeck (1981). Inside Computer Understanding: Five Programs with Miniatures. Hillsdale, NJ., Lawrence Erlbaum.Google Scholar

Scheutz, M. (2002). Agents with or without Emotions? Proceedings of the Fifteenth International Florida Artificial Intelligence Research Society Conference. 89–93.

Scheutz, M., , P Schemerhorn, et al. (2007). “First Steps toward Natural Human-Like HRI.” Autonomous Robots 22: 411–423.CrossRef Google Scholar

Searle, J. (1992). Rediscovery of The Mind. Cambridge, MA, MIT Press.Google Scholar

Searle, J. (2002). I Married A Computer. Are We Spiritual Machines? Ray Kurzweil vs. the Critics of Strong A.I. J. W. Richards. Seattle, WA., Discovery Institute.Google Scholar

Searle, J. R (1980). Minds, Brains, and Programs. Mind Design II. J. Haugeland. Cambridge, Mass., MIT Press.Google Scholar

Searle, J. R (1984). Minds, Brains, and Science. Cambridge, MA., Harvard University Press.Google Scholar

Seidenberg, M. S and , M. C. MacDonald (1999). “A Probabilistic Constraints Approach to Language Acquisition and Processing.” Cognitive Science 23(4): 569–588.CrossRef Google Scholar

Sejnowski, T. and , C. Rosenberg (1987). NETtalk: a parallel network that learns to read aloud, Technical Report JHU/EECS-86/01, Johns Hopkins University.

Selfridge, O. (1959). Pandemonium: A paradigm for learning. Symposium on the Mechanization of Thought, London, HMSO.Google Scholar

Shanker, S. G (1987). AI at the Crossroads. The Question of Artificial Intelligence. B. Bloomfield. London, Croom Helm: 1–58.Google Scholar

Shannon, C. (1950). “Programming a computer for playing chess.” Philosophical Magazine 41: 256–275.Google Scholar

Shapin, S. (1994). A Social History of Truth: Civility and Science in Seventeenth-Century England. Chicago: IL, University of Chicago Press.Google Scholar

Shimojima, A. (1996). On the Efficacy of Representation. Philosophy. Bloomington, Indiana University.Google Scholar

Shultz, T. R and , W. C. Schmidt (1991). A Cascade-Correlation Model of Balance Scale Phenomenon. 13th Annual Conference of Cognitive Science Society, Erlbaum.Google Scholar

Simon, H. A (1969). The Sciences of The Artificial. Cambridge, MA, MIT Press.Google Scholar

Simon, H. A (1995). “Artificial Intelligence: an empirical science.” Artificial Intelligence 77(1): 95–127.CrossRef Google Scholar

Skinner, B. F (1985). “Cognitive Science and Behaviourism.” British Journal of Psychology 76: 33–43.CrossRef Google Scholar PubMed

Sloman, A. (2001). “Beyond Shallow Models of Emotion.” Cognitive Processing 2(1): 177–198.Google Scholar

Sloman, A. (2005a). AI in a New Millenium: Obstacles and Opportunities. IJCAI. Birmingham, UK.Google Scholar

Sloman, A. (2005b). Do Machines, Natural or Artificial, Really Need Emotions? NWO Cognition Program. Utrecht.Google Scholar

Smith, B. C (1991). “The Owl and the Electric Encyclopedia.” Artificial Intelligence 47(1–3): 252–288.CrossRef Google Scholar

Smith, B. C (1996). The Origin of Objects. Cambridge, MA, The MIT Press.Google Scholar

Smith, B. C (1997) One Hundred Billion Lines of C++. Accessed October 15, 2005 from: http://www.ageofsignificance.org/people/bcsmith/papers/smith-billion.html.

Smith, B. C (1999). Situatedness. MIT Encyclopedia of Cognitive Science (MITECS). Cambridge, MA., MIT Press.Google Scholar

Smith, B. C (2000). Indiscrete Affairs. Vital Signs: Cultural Perspectives on Coding Life and Vitalizing Code. L. Suchman and J. Fujimura. (in press).Google Scholar

Smith, B. C (2002). Reply to Dennett. Philosophy of Mental Representation. H. Clapin. Oxford, Oxford University Press: 237–266.Google Scholar

Smith, B. C (forthcoming). The Age of Significance: Introduction. Cambidge, MA, The MIT Press.Google Scholar

Smolensky, P. (1988). “On the proper treatment of connectionism.” Behavioral and Brain Sciences 11: 1–74.CrossRef Google Scholar

Smolensky, P. (1999). “Grammar-based connectionist approaches to language.” Cognitive Science 23: 589–613.CrossRef Google Scholar

Star, L. S., Ed. (1995). Ecologies of Knowledge Work and Politics in Science and Technology. SUNY Series in Science, Technology, and Society. New York: NY, SUNY.Google Scholar

Steedman, M. (1999). “Connectionist Sentence Processing in Perspective.” Cognitive Science 23(4): 615–634.CrossRef Google Scholar

Steels, L. (1990). Cooperation between distributed agents through self-organization. Decentralized AI. Y. Demazeau and J. P. Muller. Amsterdam, North-Holland: 175–196.Google Scholar

Stewart, J. (1992). Life=Cognition: The epistemological and ontological significance of Artificial Life. First European Conference on Artificial Life, MIT Press.Google Scholar

Suchman, L. (1987). Plans and Situated Actions. Cambridge, UK., Cambridge University Press.Google Scholar

Suchman, L. A (2007). Human-Machine Reconfigurations. Cambridge, Cambridge University Press.Google Scholar

Thelen, E. and , L. B. Smith (1994). A dynamic systems approach to the development of cognition and action. Cambridge, MA., MIT Press.Google Scholar

Thompson, R. K. R., D. L. Oden, et al. (1997). “Language-Native Chimpanzees (Pan troglodytes) Judge Relations Between Relations in a Conceptual Matching-to-sample Task.” Journal of Experimental Psychology: Animal Behavior Processes 23: 31–43.Google Scholar

Toole, B. A (1992). Ada, the Enchantress of Numbers. Mill Valley: CA, Strawberry Press.Google Scholar

Townsend, J. T and , J. Busemeyer (1995). Dyamic Representation of Decision-Making. Mind as Motion. R. F. a. T. v. G. Port. Cambridge, MA., MIT Press: 101–119.Google Scholar

Turing, A. M (1936). On Computable Numbers, with an Application to Entscheidungsproblem. London Mathematical Society.Google Scholar

Turing, A. M (1950). “Computing Machinery and Intelligence.” Mind 59: 433–460.CrossRef Google Scholar

Turing, A. M (1953). Digital Computers Applied to Games. Faster than Thought. B. V. Bowden. London, UK, Pitman.Google Scholar

Turkle, S. (1985). The Second Self: Computers and The Human Spirit. New York, NY, Simon and Schuster.Google Scholar

Turkle, S. (1995). Life on the Screen: Identity in the Age of Internet. New York, N.Y., Simon & Schuster.Google Scholar

van Gelder, T. (1998). “The dynamical hypothesis in cognitive science.” Behavioral and Brain Sciences 21(5): 615–628.Google Scholar PubMed

Varela, F. J., , E Thompson, et al. (1991). The Embodied Mind: Cognitive Science and Human Experience. Cambridge, Mass., MIT Press.Google Scholar

Foerster, H. (1970). Thoughts and Notes on Cognition. Cognition: A multiple view. P. L. Garvin. New York, Spartan Books: 25–48.Google Scholar

Vygotsky, L. (1986). Thought and Language. Cambridge, Mass., MIT Press Translations.Google Scholar

Weizenbaum, J. (1976). Computer Power and Human Reason. San Francisco, CA, W. H. Freeman.Google Scholar

Wellman, B. (2001). “Computer Networks as Social Networks.” Science 293: 2031–2034.CrossRef Google Scholar PubMed

Wellman, H. M and , S. A. Gellman (1992). “Cognitive Development: Foundational theories of core domains.” Annual Review of Psychology 43: 337–375.CrossRef Google Scholar PubMed

Wiener, N. (1948). Cybernetics. New York, Wiley.Google Scholar PubMed

Wills, L. M and , J. L. Kolodner (1996). Toward More Creative Case-Based Design Systems. Case-Based Reasoning: Experiences, Lessons, and Future Directions. D. B. Leake. Menlo Park, CA., AAAI Press/MIT Press: 81–91.Google Scholar

Wilson, E. O (1971). The Insect Society. Cambridge, MA., Harvard University Press.Google Scholar

Winner, L. (1986). The Whale and The Reactor: A Search for Limits in an Age of High Technology. Chicago, IL, University of Chicago Press.Google Scholar

Winograd, T. (1972). Understanding Natural Language. New York, Academic Press.Google Scholar

Winograd, T. and , F. Flores (1986). Understanding Computers and Cognition: A New Foundation for Design. Norwood, N.J., Ablex.Google Scholar

Wittgenstein, L. (1953). Philosophical Investigations. New York, Blackwell.Google Scholar

Woods, W. A (1975). What's in a link? Foundations for semantic networks. Representation and Understanding: Studies in Cognitive Science. D. G. Bobrow and A. M. Collins. New York, Academic Press: 35–82.Google Scholar

Woolgar, S. (1985). “Why Not a Sociology of Machines? The Case of Sociology and Artificial Intelligence.” Sociology 19(4): 557–572.CrossRef Google Scholar

Woolgar, S. (1987). Reconstructing Man and Machine: A Note on Sociological Critiques of Cognitivism. The Social Construction of Technological Systems. T. H. W. Bijker, and T. Pinch. Cambridge, MA., MIT Press: 311–328.Google Scholar

Woolgar, S. (1995). Representation, Cognition, and Self: What Hope for the Integration of Psychology and Sociology? Ecologies of Knowledge: Work and Politics in Science and Technology. S. L. Star. New York State University of New York Press: 154–179.Google Scholar

Zipser, M. (2002). Introduction to the Theory of Computation. Boston, MA, PWS Publishing.Google Scholar