Copied from http://www.jimdavies.org/summaries/index.html, there you have a summary of each paper, but I was afraid of the page being removed or me forgetting about it...
Ackerman, P. L. (1988). Determinants of individual differences during skill acquisition: Cognitive abilities and information processing. Journal of Experimental Psychology: General, 117, 288-318.
Ackerman, P. L. (1992). Predicting individual differences in complex skill acquisition: Dynamics of ability determinants.
Aginsky, V. & Tarr, M. J. (2000). How are different properties of a scene encoded in visual memory? Visual Cognition, 7 (1/2/3), 147--162.
Allen, R. & Reber, A. S. (1999). Chapter 23: Unconscious intelligence. In A Companion to Cognitive Science, Bechtel, W. & Graham, G. (eds) Blackwell, Malden MA.
Allen, C., Varner, G. & Zinser, J. (2000). Prolegomena to any future artificial moral agent. Journal of Experimental & Theoretical Artificial Intelligence, 12, 251 – 261.
Amarel, S. (1968). On representations of problems of reasoning about actions, Machine Intelligence, (3), 131--171 (see this shorter summary)
Anderson, J. R. (1982). Acquisition of cognitive skill. Psychological Review, 89, 369-406. (See also this other summary and this one too.)
Anderson, J. R. (1983). A spreading activation theory of memory. Journal of Verbal Learning and Verbal Behavior, 22, 261-295. (See also this shorter summary)
Anderson, M. & Anderson, S. L. (2007). Machine ethics: Creating an ethical intelligent agent. AI Magazine, 28(4), 15-26.
Anderson, M. & McCartney, R (2003). Diagram processing: Computing with Diagrams. Artificial Intelligence. 145. pp 181--226.
Andrade, J. (2008). What does doodling do? Applied Cognitive Psychology, 24, 100-106.
Arkin, R.C. (1998), Social Behavior. In Behavior-Based Robotics,, Chapter 9. MIT Press, Cambridge, MA.
Ashcraft, M. H. & E. H. Stazyk (1981). Mental addition: A test of three verification models. Memory & Cognition. v9 pp 185-196.
Atkeson, C. G. and S. Schaal (1997). Robot Learning From Demonstration, Machine Learning: Proceedings of the Fourteenth International Conference (ICML '97), Edited by Douglas H. Fisher, Jr. pp. 12-20, Morgan Kaufmann, San Francisco, CA, 1997.
D.H. Ballard (1997) An Introduction to Natural Computation, MIT Press.
Barnard, K. & Johnson, M. (2005). Word sense disambiguation with pictures. Artificial Intelligence, 167, 13-30.
Barsalou, L.W. (1999). Perceptual symbol systems. Behavioral and Brain Sciences, 22, 577-609.
Bergmann, R; Muñoz-Avila, H; Veloso, M; Melis, E (1998). Case-Based Reasoning Applied to Planning. In CBR Technology, From Foundations to Applications, eds. Lenz, M; Bartsch-Spörl, B; Burkhard, HD; Wess, S.
Bichindaritz, & Sullivan, K. M. (1998) Reasoning from Knowledge Supported by More or Less Evidence in a Computerized Decision Support System for Bone-Marrow Post-Transplant Car. AAAI Spring Symposium in Multimodal Reasoning. Technical Report SS-98-04. 85--90 I.
Bilda Z., & Gero J. (2006). Reasoning with internal and external representations: A case study with expert architects, in R. Sun (ed), Proceedings of the Annual Meeting of Cognitive Science Society , (pp. 1020-1026). Mahaw, NJ: Lawrence Erlbaum Associates.
Bhatta, S. R. & A. K. Goel (1997). Design patterns: A computational theory of analogical design. In the Proceedings of IJCAI-97 workshop on "Using Abstraction and Reformulation in Analogy."
Bernoussi, M. (1998) Individual differences in cognitive addition. The Psychological Record. v48, pp325-332.
Berwick, R. C., Pietroski, Paul, Yankama, Beraca & Chomsky, Noam (2011). Poverty of the Stimulus Revisited. Cognitive Science, 35, 1207--1242.
Beveridge, M. & Parkins, E. (1987). Visual representation in analogical problem solving. Memory & Cognition: 15(3), 230--237.
Bhatta, S. R. & Goel, A. (1997). Learning generic mechanisms for innovative strategies in adaptive design. The Journal of the Learning Sciences, 6(4), 367--396.
Blum, Avrim L. and Furst, Merrick L. (1997) Fast Planning Through Planning Graph Analysis. Artificial Intelligence. 90. 1997. p281-300.
Bock, K. & Garnsey, S. M. (1999). Chapter 14: Language Processing. In A Companion to Cognitive Science, Bechtel, W. & Graham, G. (eds) Blackwell, Malden MA.
B. Bonet, G. Loerincs and H. Geffner (1997). A Robust and Fast Action Selection Mechanism for Planning, Proceedings of the 14th National Conference on Artificial Intelligence and 9th Innovative Applications of Artificial Intelligence Conference (AAAI-97/IAAI-97)
Bosman, E. A., & Charness, N. (1996) Age-related differences in skilled performance and skill acquisition. In F. Blanchard-Fields & T. M. Hess (Eds.), Perspectives on cognitive change in adulthood and aging (pp. 428-453). New York: McGraw-Hill.
Bowker, G. C. & Star, S. L. (1999) Sorting Things Out: Classification and Its Consequences. Parts II and III. MIT Press: Cambridge, MA.
Brooks R. (1986). A Robust Layered Control System for a Mobile Robot. IEEE Journal of Robotics and Automation, 2 (1)
Brooks, R. A. (1989). "A Robot That Walks; Emergent Behaviors from a Carefully Evolved Network," MIT AI Lab Memo 1091, February 1989.
Brooks, R. A. (1991). "Intelligence Without Reason," Proceedings of 12th Int. Joint Conf. on Artificial Intelligence, Sydney, Australia, August 1991, pp. 569--595.
Brosset, D. & Claramunt, C. (2010). An experimental ant colony approach for the geolocation of verbal route descriptions. Knowledge-Based Systems, 24, 484-491.
Brunelli, R. & T. Poggio (1993), Face Recognition: Features versus Templates, IEEE Transactions on PAMI, 15(10):1042-1052.
Bruner, J.S. (1957). Going beyond the information given. In J.S. Bruner, E, Brunswik, L. Festinger, F. Heider, K.F. Muenzinger, C.E. Osgood, & D. Rapaport, (Eds.), Contemporary approaches to cognition (pp. 41-69). Cambridge, MA: Harvard University Press. [Reprinted in Bruner, J.S. (1973). Beyond the information given (pp. 218-238). New York: Norton.]. [pages 218-222]
Buchanan, B.G. (2001). Creativity at the Metalevel: AAAI-2000 Presidential Address. AI magazine 22, (3), 13-28.
Buckner, R. L. & Petersen, S. E. (1999). Chapter 32: Neuroimaging. In A Companion to Cognitive Science, Bechtel, W. & Graham, G. (eds) Blackwell, Malden MA.
Camerer, C. F., & Johnson, E. J. (1991). The process-performance paradox in expert judgment: How can experts know so much and predict so badly? In K. A. Ericsson & J. Smith (Eds.), Towards a general theory of expertise: Prospects and limits (pp. 195-217). New York: Cambridge Press.
Carbonell, J. (1986). Derivational analogy: A theory of reconstructive problem solving and expertise acquisition. In Michalski, R., Carbonell, J., & Mitchell, T. (Eds.) Machine Learning: An Artificial Intelligence Approach. Morgan Kaufman Publishers: San Mateo, CA.
Casakin, H, & Goldschmidt, G. (1999) Expertise and the use of visual analogy: Implications for design education. Design Studies, 20:153--175.
Catrambone, R. & Holyoak, K. J. (1989) Overcoming contextual limitations on problem-solving transfer. Journal of Experimental Psychology 15:6, 1147--1156.
Cedras, C. & M. Shah (1995), Motion-Based Recognition: A Survey, IVC, 13(2):129-155.
Chandrasekaran, B. (1988) Generic Tasks as Building Blocks for Knowledge-Based Systems: The Diagnosis and Routine Design Examples. Knowledge Engineering Review, 3 (3). (see this shorter summary)
Chandrasekaran, B., Narayanan, N. H., and Iwasaki, Y. (1993). Reasoning with Diagrammatic Representations. AI Magazine, 14(2), 49-56.
Charness, N. (1981). Aging and skilled problem solving. Journal of Experimental Psychology: General, 110, 21-38.
Charness, N. (1997). Can acquired knowledge compensate for age-related declines in cognitive efficiency: Evidence from chess and bridge. Manuscript in preparation.
Chase, W. G., & Ericsson, K. A. (1982). Skill and working memory. In G. H. Bower (Ed.), The psychology of learning and motivation (Vol. 16, pp. 1-58). New York: Academic Press.
Chong, H., Tan, A., & Ng, G. (2007). Integrated cognitive architectures: a survey. Artificial Intelligence Review, 103-130.
Clayton, N.S., Russell, J. & Dickinson, A. (2009). Are animals stuck in time or are they chronesthetic creatures? Topics in Cognitive Science, 1, 59-71.
Colheart, M. (1980). Iconic memory and visible persistence. Perception and Psychophysics, 27, 183-228.
Conati, C. (2009). Intelligent Tutoring Systems: New Challenges and Directions. Proceedings of the 21st International Joint Conference on Artificial Intelligence, Pasadena, California, 2-7.
Cox, M. T. (2007). Perpetual Self-Aware Cognitive Agents. AI Magazine, 28 (1), 32-45.
Coyne, B. & Sproat, R. (2001). WordsEye: An Automatic Text-to-Scene Conversion System. In Proceedings of the 28th Annual Conference on Computer Graphics and Interactive Techniques (SIGGRAPH01), 487--496.
Craig, D. L., Catrambone, R., & Nersessian, N. J. (2003). The role of perceptually represented structure in analogical problem solving. Unpublished manuscript.
Croft, D. & Thagard, P. (2000). Dynamic imagery: A computational model of motion and visual analogy. Unpublished manuscript.
Csikszentmihalyi, M. & Robinson R. E. (1990). The Art of Seeing: An Interpretation of the Aesthetic Encounter The J. Paul Getty Museum and The Getty Education Institute for the Arts.
Dawes, R. M., Faust, D., & Meehl, P. E. (1989). Clinical versus actuarial judgment. Science, 243, 1668-1674.
Deacon, T. W. (1999). Chapter 13: Language evolution and neuromechanisms. In A Companion to Cognitive Science, Bechtel, W. & Graham, G. (eds) Blackwell, Malden MA.
T. Dean & S. Kambhampati (1996), Planning and Scheduling. The CRC Handbook of Computer Science and Engineering, A. B. Tucker (Ed.), CRC press, 1997. pp614-636.
R. Dechter (1996), Bucket Elimination: A Unifying Framework for Probabilistic Inference, in Proceedings of Uncertainty in AI, Portland, Oregon.
de Garis, H. (1990). Building Artificial Nervous Systems Using Genetically Programmed Neural Network Modules. Machine Learning: Proceedings of the Seventh International Converence, 132-139.
de Kleer J. (1984).How Circuits Work. Artificial Intelligence, 24,pp 205-280. (a shorter summary)
Do, E. Y. & Gross, M. D. (2001). Thinking with diagrams in architectural design. Artificial Intelligence Review. 15 135--149.
Donald, M. (1991) Origins of the modern mind: three stages in the evolution of cognition and culture. The President and Fellows of Harvard College. Chapter 1.
Doyle, J. (1988) Big problems for artificial intelligence. AI Magazine. 9(1) 19-22.
Driskell, J. E., Copper, C., & Moran, A. (1994). Does mental practice enhance performance?. Journal of Applied Psychology, 79(4), 481.
Dunbar, K. & Blanchette, I. (2001). The invivo/invitro approach to cognition: the case of analogy. Trends in Cognitive Sciences, 5, 334--339.
Durrant, R., and Ellis, B.J. (2003). Evolutionary psychology. In M. Gallagher, R. J. Nelson, & I. B. Weiner (Eds.) Handbook of psychology: Biological psychology, 3, 1-33.
Ellis, R. & Humphreys, G. W. (1999). Chapter 4: Perception. In Connectionist Psychology: A Text with Readings. Psychology Press.
Ericsson, K. A. (1996). The acquisition of expert performance: An introduction to some of the issues. In K. A. Ericsson (Ed.), The road to excellence: The acquisition of expert performance in the arts and sciences, sports, and games (pp. 1-50). Mahwah, NJ: Lawrence Erlbaum.
Ericsson, K. A. & Charness, N. (1997). Cognitive and developmental factors in expert performance. In P. J. Feltovich, K. M. Ford, & R. R. Hoffman (Eds.), Expertise in context: Human and machine (pp 3-41). Cambridge, MA: MIT Press.
Ericsson, K. A., & Kintsch, W. (1995). Long-term working memory. Psychological Review, 102, 211-245.
Ericsson, K. A., Krampe, R. Th., & Tesch-Roemer, C. (1993). The role of deliberate practice in the acquisition of expert performance. Psychological Review, 100, 363-406.
Ericsson, K. A., & Lehmann, A. C. (1996). Expert and exceptional performance: Evidence of maximal adaptation to task. Annual Review of Psychology, 47, 273-305.
Ericsson, K. A., & Staszewski, J. J. (1989). Skilled memory and expertise: Mechanisms of exceptional performance. In D. Klahr & K. Kotovsky (Eds.), Complex information processing: The impact of Herbert A. Simon (pp. 235-267). Hillsdale, NJ: Lawrence Erlbaum.
Eysenck, M. W. & Keane, M. T. (1995). Chapter 4: Theories of perception, movement, and action. In Cognitive Psychology: A Student's Handbook, Lawrence Erlbaum, Hillsdale, USA.
Falkenhainer, B., K. D. Forbus, D. Gentner (1990). The Structure mapping engine: algorithm and examples. Artificial Intelligence (41) pp1-63.
Falkenhainer, B.,(1990) A unified approach to explanation and theory formation. In Shrager, J. & Langley, P. (eds.) Computational Models of Scientific Discovery and Theory Formation. Morgan Kaufman: San Meteo, CA. pp 157--196.
Faltings, B. and Sun, K. (1995). "FAMING: Supporting Innovative Mechanism Shape Design," Computer-Aided Design.
Farah, M.J. (2000). The neural bases of mental imagery. In M,S. Gazzaniga (Ed), The cognitive neurosciences (2nd ed., 965-974). Cambridge, MA: MIT Press.
Ferguson, R. W. & Forbus, K. D. (1998) Telling juxtapositions: Using repetition and alignable difference in diagram understanding. In Holyoak, K., Gentner, D., & Kokinov, B. (Eds.) Advances in Analogy Research, 109--117. Sofia: New Bulgarian University.
Ferguson, R. W., & Forbus, K. D. (2000). GeoRep: A flexible tool for spatial representation of line drawings, Proceedings of the 18th National Conference on Artificial Intelligence. Austin, Texas: AAAI Press.
Fermuller, C.& Y. Aloimonos (1995). Vision and Action, IVC, 13(10):725-744
Fisher, D.H. (1987), Knowledge Acquisition via Incremental Conceptual Clustering, Machine Learning 2:139-172, reprinted in Shavlik & Dietterich (eds.), Readings in Machine Learning, section 3.2.1.
Fisher, K. (Winter 2011). How people talk with robots: designing dialogue to reduce user uncertainty. AI Magazine, 32, 4. 31--38.
Forbus, K.D, Ferguson, W. R. Gentner, D. (1994). Incremental Structure Mapping, Proceedings of the 14th Annual Conference of the Cognitive Science Society, 313--318.
Forbus, K. D. (1995). Qualitative spatial reasoning framework and frontiers. In Diagrammatic Reasoning, Glasgow, J., Narayanan, N. H. A., and Chandrasekaran, B., AAAI Press, 1995. pp 183--202.
Franklin, M. S., & Zyphur, M. J. (2005). The Role of Dreams in the Evolution of the Human Mind. Evolutionary Psychology, 3: 59-78.
Freksa C. & Zimmermann K. (1993). On the Utilization of Spatial Structures for Cognitively Plausible and Efficient Reasoning. Proceedings of the Workshop on Spatial and Temporal Reasoning, 13th International Joint Conference on Artificial Intelligence, Chamberg, France, 1993, pp. 61-66.
Frith, C. D. (1999). Chapter 29: Deficits and pathologies. In A Companion to Cognitive Science, Bechtel, W. & Graham, G. (eds) Blackwell, Malden MA.
Funt, B. V. (1980). Problem-solving with diagrammatic representations. Artificial Intelligence 13, No. 3, pp. 201--230.
Galantucci, B. (2005). An Experimental Study of the Emergence of Human Communication Systems, Cognitive Science, 2005, vol. 29, 737-767.
Gardner, H. (1995). Expert performance: Its structure and acquisition: Comment. American Psychologist, 50, 802-803.
Gentner, D. (1983) Structure-mapping: A theoretical framework for analogy. Cognitive Science. 7 (2), pp155-170. (see also this shorter summary.)
Gero, John S. (1990). Design Prototypes: A Knowledge Representation Schema for Design. AI Magazine, 11:4, 26-36.
Geschwind, N. (1980). Neurological Knowledge and Complex Behaviors. Cognitive Science, 4, 185-193.
Gibson, E.J. (1977). How perception really develops: A view from outside the network. In Laberge & Samuels, (Eds.). Basic processes in reading: Perception and comprehension (pp. 155-173). Mahwah, NJ: Erlbaum.
Gick, M. L., & Holyoak, K. J. (1980). Analogical problem solving. Cognitive Psychology 12, 306--355.
Giere, R. N. (2000). Scientific cognition as distributed cognition. Manuscript draft.
Gigerenzer, G and Goldstein, D. (1996). Reasoning the Fast and Frugal Way: Models of Bounded Rationality. Cognitive Science 103(4), 650-666.
Gilbert, D. T. (1991). How Mental Systems Believe. American Psychologist, 46(2), 107-119.
Glasgow, J. I. (1993). The imagery debate revisited: A computational perspective. Computational Intelligence 9:4, 309--333.
Glasgow, J., Epstein, S., Meurice, N., & Vercauteren, D. (2004). Spatial motifs in design. In Proceedings of the Third International Conference on Visual and Spatial Reasoning in Design Massachusettes Institute of Technology, Cambridge, MA.
Glasgow, J., Fortier, S., Conklin, D., Allen, F, & Leherte, L. (2004). Knowledge representation for molecular scene analysis. Unpublished manuscript.
Glasgow, J., Narayanan, N. H., Chandrasekaran, B. (1995). Diagrammatic Reasoning: Cognitive and Computational Perspectives. AAAI Press/MIT Press: Cambridge, MA.
Glasgow, J. & Papadias, D. (1998). Computational imagery. In Thagard, P. Mind Readings. Cambridge, MA: MIT Press.
Gobert, J.D. & Clement, J.C. (1999) Effects of Student-Generated Diagrams versus Student-Generated Summaries on Conceptual Understanding of Causal and Dynamic Knowledge in Plate Tectonics. Journal of Research in Science Teaching, Vol 36, No. 1, 39-53.
Goel, A., Bhatta, S. & Stroulia, E. (1997) Kritik: An Early Case-Based Design System. In Maher, M. and Pu, P. (Eds.)Issues and Applications of Case-Based Reasoning in Design, Mahwah, NJ: Erlbaum, pages 87--132.
Goertzel, B. (2007). Human-level artificial general intelligence and the possibility of a technological singularity. A reaction to Ray Kurzweil's The Singularity Is Near, and McDermott's critique of Kurzweil. Artificial intelligence, 171, 1161-1173.
Gomes, P., Seco, N., Pereira, F. C., Paiva, P., Carreiro, P., Ferreira, J. L., and Bento, C. (2003) The importance of retrieval in creative design analogies. in Creative Systems: Approaches to Creativity in AI and Cognitive Science. Workshop program in the Eighteenth International Joint Conference on Artificial Intelligence. pp. 37--45. Acapulco, Mexico.
Gosselin, F. Schyns, P.(2004). A picture is worth thousands of trials: rendering the use of visual information from spiking neurons to recognition.Cognitive Science, 28, 141-146.
Graesser, A. C., Person, N. K., & Magliano, J. P. (1995). Collaborative dialogue patterns in naturalistic one-on-one tutoring. Applied Cognitive Psychology, vol. 9, pp495-522.
Graesser, A. & Tipping, P. (1999). Chapter 24: Understanding Texts. In A Companion to Cognitive Science, Bechtel, W. & Graham, G. (eds) Blackwell, Malden MA.
Granger, R. (2006). Engines of the brain: The computational instruction set of human cognition. AI Magazine: 27(2), 15-33.
Gray, C. & G. Mulhern (1995). Does children's memory for addition facts predict general mathematical ability? Perceptual and Motor Skills. v81, pp163-167.
Greene, J.D., Nystrom, L.E., Engell, A.D., Darley, J.M., & Cohen, J.D. (2004). The neural bases of cognitive conflict and control in moral judgment. Neuron, 44, 389-400.
Grudin, J. (2009). AI and HCI: Two fields divided by a common focus. AI magazine, 30(4), 48-57.
Geurts, B. (2003). Reasoning with quantifiers. Cognition, 86, 223-251.
Guarini, M. (2009). Computational theories of mind, and Fodor's analysis of neural network behaviour. Journal of Experimental & Theoretical Artifical Intelligence. Vol 21 (2). 137--153.
Guesgen, H. W. (1989). Spatial reasoning based on Allen's temporal logic. International Computer Science Institute technical report. TR-89-049. 1947 Center St, Suite 600, Berkeley, CA.
Gupta, A.[Amarnath], Jain, R.[Ramesh], Visual Information Retrieval, CACM(40), No. 5, May 1997, pp. 70-79.
Gutman, J., Fukuchi, M., & Fujita, M. (2005) Real-time path planning for humanoid robot navigation. IJCAI-05, 1232-1238.
Haber, R. N. (1983). The impending demise of the icon: A critique of the concept of iconic storage in visual information processing. The Behavioral and Brain Sciences, 6, 1-54.
Haberlandt, K. (1999). Chapter 1: Introduction. In Human Memory: Exploration and Applications, Allyn & Bacon. Needham Heights, MA.
Haberlandt, K. (1999). Chapter 5: Memory for skills. In Human Memory: Exploration and Applications, Allyn & Bacon. Needham Heights, MA.
Haddawy, P. (1996). Focussing Attention in Anytime Decision-Theoretic Planning, SIGART Bulletin, Vol. 7, No. 2.
K. Hammond (1989), Case-Based Planning: Viewing Planning as a Memory Task, chapters 1, Academic Press.
K. Hammond (1989), Case-Based Planning: Viewing Planning as a Memory Task, chapters 2, Academic Press.
K. Hammond (1989), Case-Based Planning: Viewing Planning as a Memory Task, chapter 3, Academic Press.
Hampson, P. J. & Morris, P. E. (1996). Chapter 8: Planning and actions: Successes and failures. In Understanding Cognition, Blackwell, Cambridge MA.
Hampson, P. J. & Morris, P. E. (1996). Chapter 13: Connectionism. In Understanding Cognition, Blackwell, Cambridge MA.
Hawley-Dolan, A. & Winner, E. (2011). Seeing the mind behind the art: people can distinguish abstract expressionist paintings from highly similar paintings by children, chimps, monkeys, and elephants. Psychological Science, X, 1-7.
Hayes, P. (1973) The Frame Problem and Related Problems in AI. Artificial and Human Thinking, A. Elithorn and D. Jones (eds.), Jossey-Bass (see also this shorter summary)
Hayes-Roth, B. and F. Hayes-Roth (1979) A Cognitive Model of Planning. International Joint Conference on Artificial Intelligence (See also this shorter summary.
Hayward, W.G. & Tarr, M.J. (1995). Spatial language and spatial representation. Cognition, 55, 39-84.
Hekkert, P. & Snelders, D. & van Wieringen, P.C.W. (2003) ‘Most Advanced, yet acceptable’: Typicality and novelty as joint predictors of aesthetic preference in industrial design. British Journal of Psychology, 94, 111-124.
Hegarty, M. (1992). Mental animation: Inferring motion from static displays of mechanical systems. Journal of Experimental Psychology: Learning, Memory, and Cognition. 18(5), 1084--1102.
Herberg et al. (2008). Audience-contingent variation in action demonstration for humans and computers. Cognitive Science, 32, 1003-1020.
C. Hewitt, PLANNER: A Language for Proving Theorems in Robots. International Joint Conference on Artificial Intelligence, 1969.
Hinton, G. (1979). Some demonstrations of the effects of structural descriptions in mental imagery. Cognitive Science, 3, 231--250.
Hinricks, T.R., & Forbus, K.D.(2011). Transfer learning through analogy in games. AI Magazine, 32(1), 70-83.
Hobson, J. A. & McCarley, R. W. (1977). The brain as a dream state generator: An Activation- Synthesis Hypothesis of the dream process. The American Journal of Psychiatry, 134:12, 1335-1348.
Hofstadter, D. R.& Mitchell, M. (1995). The copycat project: A model of mental fluidity and analogy-making. In Hofstadter, D. and the Fluid Analogies Research group, Fluid Concepts and Creative Analogies. Basic Books. Chapter 5: 205--267.
Holyoak, K. J., & Thagard, P. (1989). A computational model of analogical problem solving. In S. Vosniadou & A. Ortony (Eds.), Similarity and analogical reasoning (pp. 242-266). Cambridge: Cambridge University Press.
Holyoak, K. J. & Thagard, P. (1989). Analogical mapping by constraint satisfaction. Cognitive Science, 13: 295--355.
Holyoak, K. J. & Thagard, P. (1997). The analogical mind. American Psychologist.52(1)35-44.
Huang, L., Galinsky, A. D., Gruenfeld, D. H., & Guillory, L. E. (2011). Powerful postures versus powerful roles: Which is the proximate correlate of thought and behavior? Psychological Science, 22(1), 95-102.
Hunt, E. & Agnoli, F. (1991). The Worfian hypothesis: A cognitive psychology perspective. Psychological Review, 98 (3). pp 377-389.
Huttenlocher, J., Vasilyeva M. (2009). How toddlers represent enclosed spaces. Cognitive Science, 27, 749-766.
Jain, R. (1997), Visual Information Management, CACM, 40(12):30-32.
Johnson-Laird, P.N. and Lee, N.Y.L. (2006). Are there cross-cultural differences in reasoning? Proceedings of the 28th Annual Conference of the Cognitive Science Society, (pp. 459-464).
Jurisica, I. & Glasgow, J. (2000). Extending case-based reasoning by discovering and using image features in in-vitro fertilization. In B. Bryant, J. Carroll, E. Damiani, H. Haddad, & D. Oppenheim (Eds.) Proceedings of the 2000 ACM symposium on Applied computing - Volume 1 March 19-21, Villa Olmo,
Jurisica, I. & Glasgow, J. (2004). Applications of case-based reasoning in molecular biology. AI Magazine, 25(1), 85--95.
Kadar-Cabelli, S. (1985). Purpose-directed analogy. Proceedings of the seventh annual conference of the Cognitive Science Society. Lawrence Erlbaum publishers.
H. Kautz and B. Selman (1996). Pushing the Envelope: Planning, Propositional Logic and Stochastic Search, Proceedings of the Thirteenth National Conference on Artificial Intelligence (AAAI-96), Portland, OR.
Kellman, P. & Arterberry, M.E. (1998). Chapter 5: Object Perception. The cradle of knowledge: Development of perception in infancy. Cambridge: M.I.T. Press.
C.A. Knoblock (1994). Automatically Generating Abstractions for Planning, Artificial Intelligence, 68(2).
J. Kolodner and D. Leake, A Tutorial Introduction to Case-Based Reasoning. To appear in Case-Based Reasoning: Experiences, Lessons, and Future Directions, D. Leake (ed.), AAAI Press, 1996. (See also this longer summary.)
Kool, W., McGuire, J., Rosen, Z. and Botvinick M. (2010). Decision Making and the Avoidance of Cognitive Demand. Journal of Experimental Psychology: General, 1-18.
Kosslyn, S. M. & Shwartz, S. P. (1977). A simulation of visual imagery. Cognitive Science 1, 265--295.
Kosslyn, S. M. (1994) Image and Brain: The Resolution of the Imagery Debate. MIT Press, Cambridge, MA.
Krampe, R. Th., & Ericsson, K. A. (1996). Maintaining excellence: Deliberate practice and elite performance in younger and older pianists. Journal of Experimental Psychology: General, 125, 331-359.
Kuhn, T. H. The Structure of Scientific Revolutions
Laeng, B. & Teodorescu, D. (2002). Eye scanpaths during visual imagery reenact those of perception of the same visual scene. Cognitive Science, 26, 207-231.
Laird J., Newell A., and Rosenbloom P. (1987) SOAR: An Architecture for General Intelligence. Artificial Intelligence, 33.
Lakoff, G. & Kovecses, Z. (1987). Chapter 8: The cognitive model of anger inherent in American English. In Cultural Models in Language and Thought, Holland, D. & Quinn, N. (eds.)
Lakoff, G. & M. Johnson. (1999) Philosophy In The Flesh: The Embodied Mind and Its Challenge to Western Thought. Basic Books.
Landaur, T. K. (1998). Learning and Representing verbal meaning: The latent semantic analysis theory. Current Directions is Psychological Science, 7 (5) pp 161-164
Langston, W., Kramer, D. C., & Glenberg, A. M. (1998). The representation of space in mental models derived from text. Memory and Cognition, 26, 247-262.
Larkin, J., McDermott, J., Simon, D. P., & Simon, H. A. (1980). Expert and novice performance in solving physics problems. Science, 208, 1335-1342.
Larkin, J. & Simon, H. (1987) Why a diagram is (sometimes) worth ten thousand words. Cognitive Science, 11:65-99.
Lebiere, C. (1998) The dynamics of cognition: An ACT-R model of cognitive arithmetic. Carnegie Mellon University technical report #CMU-CS-98-186.
Leherte, L., Glasgow, J., Baxter, K., Steeg, E., and Fortier, S. (1997). Analysis of three-dimensional protein images. Journal of Artificial Intelligence Research, 7, 125--159.
Lien, M., Ruthruff, E., and Johnston, J. (2006). Attentional Limitations in Doing Two Tasks at Once: The Search For Exceptions. Current Directions in Psychological Science. Vol 15 (2). 89--93.
Lenat, D. (1977). The Ubiquity of Discovery. Artificial Intelligence, 9.
Lenat, D. & R. Guha (1990)., Building Large Knowledge Based Systems: Representation and Inference in the Cyc Project. Addison-Wesley Publishing. (See also this shorter summary)
Levesque, Hector J. (1986). Making Believers out of Computers. Artificial Intelligence, 30, 81-108.
Liang, Z. (1993). Tissue classification and segmentation of MR images. IEEE Engineering in Medicine and Biology. March, pp 81--85.
Litt, A., Eliasmith, C., Kroon, F.W., Weinstein, S. and Thagard, P. (2006)Is the Brain a Quantum Computer?. Cognitive Science, 30: 593--603.
Lindeman, M., Aarnio, K. (2007). Superstitious, magical, and paranormal beliefs: An integrative model. Journal of Research in Personality, 41, 731-744.
Loftus, G. R., Johnson, C. A., & Shimamura, A. P. (1985). How much is an icon worth? Journal of Experimental Psychology: Human Performance and Perception, 11, 1-13.
Loftus, G. R., & Duncan, J., & Gehrig, P. (1992). On the time course of perceptual information that results from a brief visual presentation. Journal of Experimental Psychology: Human Performance and Perception, 18, 530-549.
Logan, G. D. (1992). Attention and preattention in theories of automaticity. American Journal of Psychology, 105, 317-339.
Luger, G. F. (1994). Chapter 13: Language representation and processing. In Cognitive Science: The Science Of Intelligent Systems. Academic Press, San Diego, CA
Maes, P. (1990), Situated Agents Can Have Goals, Robotics and Autonomous Systems, 6:49-70.
D. Marr, Vision. Freeman Publishers, 1982.
Marshall, J. B. (2002). Metacat: A self-watching model of analogy-making and perception. In W.D. Gray & C.D. Schunn (Eds.), Proceedings of the 24th Annual Conference of the Cognitive Science Society (pp. 631-636). Mahaw, NJ: Lawrence Erlbaum Associates.
Matlock, T., Ramscar, M. & Boroditsky, L. (2005). On the Experiential Link Between Spatial and Temporal Language. Cognitive Science, 29(4). 655--664.
Matric, M. J. (1997). Behaviour-based control: examples from navigation, learning, and group behaviour. Journal of Experimental & Theoretical Artificial Intelligence, 9 (2-3), 323-336.
Mattingly, C., Lutkehaus, N.C., & Throop, C.J. (2008). Bruner's search for meaning: A conversation between psychology and anthropology. Ethos, 36, 1-28.
McCarthy, J. (1995). What has AI in Common with Philosophy?. Proceedings of the 14th International Joint Conference on AI, Montreal, 2041-2042.
McCarthy, J., Minsky, M., Sloman, A., Gong, L., Lau, T., Morgenstern, L., Mueller, E., Riecken, D., Singh, M., Singh, P. (2002). An Architecture of Diversity for Commonsense Reasoning. IBM Systems Journal, 41, 3, 530-539.
D. McDermott, Planning and Acting. Cognitive Science, 2, 1978. See also this longer outline
D. McDermott and J. Doyle (1980). Nonmonotonic logic 1, Artificial Intelligence", Vol. 13, p41-72, 1980. (see this shorter summary)
McGraw, Gary & Douglas R. Hofstadter. (1993) Perception and Creation of Alphabetic Style. In Artificial Intelligence and Creativity: Papers from the 1993 Spring Symposium, AAAI Technical Report SS-93-01, AAAI Press.
McGraw, Gary, Daniel Drasin. (1993). Recognition of Gridletters: Probing the Behavior of Three Competing Models. In Proceedings of the Fifth Midwest AI and Cognitive Science Conference, pages 63-67, April 1993.
McGraw, Gary, John Rehling & Robert Goldstone (1994). Letter Perception: Toward a conceptual approach. In the Proceedings of the Sixteenth Annual Conference of the Cognitive Science Society, pages 613-618, Atlanta, GA, August 1994.
McNamara, T. P. (1986). Mental representations of spatial relations. Cognitive Psychology 18. 87--121.
Miles, H. L. (1983) Apes and language: The search for communicative competence. In Language in Primates: Perspectives and Implications, J. De Luce & H. T. Wilder (eds.). Springer-Verlag, New York. pp 43-61.
Miles, L. (1990) The cognitive foundations for reference in a signing orangutan. In "Language" and intelligence in monkeys and apes by Parker, S. T. and K. R. Gibson (Eds) 1990. p 511-539.
Miles, L. W. & S. E. Harper (1994) "Ape language" studies and the study of human language origins. in Hominid Culture in Primate Perspective, by Quiatt, D. D. & J. Itani (eds). University Press of Colorado. pp253-278
M. Minsky, A Framework for Representing Knowledge. The Psychology of Computer Vision, P. H. Winston (ed.), McGraw-Hill 1975.
Minsky, M., Singh, P. & Sloman, A. (2004). The St. Thomas common sense symposium: designing architectures for human-level intelligence. American Association for Artificial Intelligence, 25(2), 113-124.
Mitchell, T., R. Keller, and S. Kedar-Cabelli, Explanation-Based Generalization: A Unifying View. Machine Learning, 1, 1982. (see also this shorter summary)
Mobbs, D., & Watt, C. (2011). There is nothing paranormal about near-death experiences: how neuroscience can explain seeing bright lights, meeting the dead, or being convinced you are one of them. Trends In Cognitive Science, 15, 10, 447-449
Monaghan, J. M. & Clement, J. (1999). Use of computer simulation to develop mental simulations for understanding relative motion concepts. International Journal of Science Education 21(9), 921--944.
Morrow, D. G., Leirer, V. O., & Altieri, P. A. (1992). Aging, expertise, and narrative processing. Psychology and Aging, 7, 376-388.
Narayanan, N. H., Suwa, M. & Motoda, H. (1994). How things appear to work: Predicting behaviors from device diagrams. Proceedings of the 12th National Conference on Artificial Intelligence, AAAI Press, pp. 1161-1167.
Nau, D.S., Lustrek, M., Parker, A., Bratko, I. & Gams, Matjaz (2010). When is it better not to look ahead? Artificial Intelligence, 173, 1323-1338.
Nersessian, N. J. (1984). Maxwell's `Newtonian aether-field'. In Nersessian, N. J. Faraday to Einstein: Constructing Meaning in Seientific Theories. Kluwer, Dordrecht. pp 68-93.
Nersessian, N. J. (1992). How do scientists think? Capturing the dynamics of conceptual change in science. In Giere, R. N. (ed.) Cognitive Models of Science. 5--22. University of Minnesota Press. Minneapolis, MN.
Nersessian, N. J. (1994). Opening the black box: Cognitive science and the history of science. In Thackray, A. (ed.) Constructing Knowledge in the History of Science. Osiris 10, 1995.
Nersessian, N. J. (1997) Abstraction via generic modeling in concept formation in science. In Idealization and Abstraction in Science. M. R. Jones and N. Cartwright (eds.). Amsterdam: Editions Rodopi, 1997.
Nersessian, N. J. (1998). Model-based reasoning in conceptual change. in Model-Based Reasoning in Scientific Discovery, L. Magnani, N. Nersessian & P. Thagard (eds). Plenum.
A. Newell and H. Simon, GPS, A Program that Simulates Human Thought. Computers and Thought, E. A. Feigenbaum and J. Feldman (eds.), R. Oldenbourg KG., 1963.
A. Newell, The Knowledge Level. Artificial Intelligence, 18 (1), 1982.
Newell, A. & H.A. Simon (19??), The Theory of Human Problem Solving. Reprinted in Readings in Cognitive Science, Collins & Smith (eds.), section 1.3, pp. 33. (see also this shorter summary)
Niyogi, S. A. (1995). Deducing Visual Relationships from Attentional Representations. AAAAI Fall Symposium Series in Computational Models for Integrating Language and Vision. 63-69.
Novick, L. R. & Holyoak, K. J. (1991). Mathematical problem solving by analogy. Journal of Experimental Psychology: Learning, Memory, and Cognition. Vol 17 (3). 398--415.
Ormerod, T.C., Chronicle, E.P. & MacGregor, J.N. (2006). Asymmetrical analogical transfer in insight problem solving. In R. Sun (Ed.), Proceedings of the 28th Annual Conference of the Cognitive Science Society, (pp. 1899-1904). Mahwah, N.J.: Lawrence Erlbaum Associates, Inc.
Parker, L. E. (1998). ALLIANCE: An architecture for fault tolerant multirobot cooperation. IEEE Transactions on Robotics and Automaton. v14, no. 2, April 1998.
Palmer, S. E. (1975). Visual perception and world knowledge: Notes on a model of sensory-cognitive interaction. In D. A. Norman & D. E. Rumelhart (Eds.), Explorations in cognition (pp. 279-307). San Francisco: Freeman.
Partee, B. H. (1999). Semantics. In The MIT Encyclopedia of the Cognitive Sciences, Wilson, R. A. & Keil, F. C. (eds.) MIT Press, Cambridge, MA. pp 739-741.
Pearson, David G. (2007). Mental imagery and creative thought. Proceedings of the British Academy, 147, 187-212.
Perner, P. (2001). Why case-based reasoning is attractive for image interpretation. In D. Aha and I Watson (Eds.) Case-Based Reasoning Research and Development. Springer-Verlag, LNAI 2080, 27--44.
Peterson, J., K. Mahesh & A. Goel (1994). Situating natural language understanding within experience-based design. Int. J. Human-Computer Studies. 41, 881-913.
Pezzulo, G. & Giangulielmo, C. (2004). A Pandemonium can have Goals. Proceedings of the Sixth Annual International Conference on Cognitive Modelling (ICCM 2004). 237-242.
Ponzetto, S.P., & Strube, M (2007). Knowledge Derived From Wikipedia For Computing Semantic Relatedness. Journal of Artificial Intelligence Research, 30, 181-212.
Pylyshyn, Z. W. (1978). Imagery and artificial intelligence. from C.W. Savage, ed., Perception and Cognition. Issues in the Foundations of Psychology, Minnesota Studies in the Philosophy of Science, vol. 9, Minneapolis: University of Minnesota Press) pp. 19-55
Pynadath D. V. & Marsella, S. C. (2005) PsychSim: Modeling Theory of Mind with Decision-Theoretic Agents. Proceedings of the International Joint Conference on Artificial Intelligence. 1181--1186.
Quillian, M. (1968). Semantic Memory, in M. Minsky (ed.), Semantic Information Processing, pp 227-270, MIT Press; reprinted in Collins & Smith (eds.), Readings in Cognitive Science, section 2.1 (see also this shorter summary)
J.R. Quinlan (1986), Induction of Decision Trees, Machine Learning 1:81-106; reprinted in Shavlik & Dietterich (eds.), Readings in Machine Learning, section 2.2.1.
Ram, A. & Leake, D. (1995). Learning, Goals, and Learning Goals. In Goal-Driven Learning. by A. Ram & D. Leake, (eds) Chapter 1. MIT Press/Bradford Books, Cambridge, MA.
Rafael Ramirez and Amaury Hazan, A Learning Scheme for Generating Expressive Music Performances of Jazz Standards, IJCAI, pp. 1628-1629, 2005.
Reeves, L. M. & Weisberg, R. W. (1994). The role of content and abstract information in analogical transfer. Psychological Bulletin. Vol. 115 (3). 381--400.
Rehling, J., & Hofstadter, D. (1997) The Parallel Terraced Scan: An Optimization for an Agent-Oriented Architecture. 1997 IEEE International Conference on Intelligent Processing Systems.
Resnik, P. (1995) Using Information Content to Evaluate Semantic Similarity in a Taxonomy. International Joint Conference for Artificial Intelligence (IJCAI-95). 448-453.
Reynolds, C. W. (1987), Flocks, herds, and schools: A distributed behavioral model, Computer Graphics, 21(4):25-34.
Richardson, D. C., Spivey, M. J., Edelman, S. & Naples, A. J. (submitted). Image schemas of concrete and abstract verbs: Experimental evidence.
Roediger, H. L. & Goff, L. M. (1999). Chapter 17: Memory. In A Companion to Cognitive Science, Bechtel, W. & Graham, G. (eds) Blackwell, Malden MA.
Rosen, V. M., & Engle, R. W. (1998). Working memory capacity and suppression. Journal of Memory and Language, 39, 418-436.
Rowley, H.A., S. Baluja, & T. Kanade (1998), Neural Network-Based Face Detection, IEEE Transactions on PAMI, 20(1):23-38.
Roy, D. and Reiter, E. (2005). Connecting Language to the world. Artificial Intelligence, 167, 1-12.
Russell, S. (1995). Rationality and Intelligence. Artificial Intelligence, 94, 57–77.
Russell, S. & P. Norvig (1994) Probabilisitc Reasoning Systems, Chapter 15: Artificial Intelligence: A Modern Approach.
S. Russell and E. Wefald (1991). Do the right thing : studies in limited rationality (Chapter 1: Limited Rationality), MIT Press, Cambridge, MA.
S. Russell and E. Wefald (1991). Do the right thing : studies in limited rationality (Chapter 2: Metareasoning Architectures), MIT Press
S. Russell and E. Wefald (1991). Rational Metareasoning (Chapter 3: Do the Right Thing), MIT Press
S. Russell and E. Wefald (1991). Do the right thing : studies in limited rationality (Chapter 4: Application to Game-Playing), MIT Press
S. Russell and E. Wefald (1991). Do the right thing : studies in limited rationality (Chapter 5: Application to Problem-Solving Search), MIT Press
Salthouse, T. A. (1984). Effects of age and skill in typing. Journal of Experimental Psychology: General, 13, 345-371.
Salthouse, T. A. (1989). Aging and skilled performance. In A. M. Colley & J. R. Beech (Eds.), Acquisition and performance of cognitive skills (pp. 247-263). Chichester, UK: John Wiley & Sons.
Salthouse, T. A. (1990). Working memory as a processing resource in cognitive aging. Developmental Review, 10, 101-124.
Salthouse, T. A., & Mitchell, D. R. D. (1990). Effects of age and naturally occurring experience on spatial visualization performance. Developmental Psychology, 26, 845-854.
Sanderson, Y. B. (2011). Color Charts, Esthetics, and Subjective Randomness. Cognitive Science, 36, 142-149.
Schacter, D.L.(1992). Understanding Implicit Memory: A Cognitive Neuroscience Approach. American Psychologist, 47(4), 559-569.
Schank, R. C. (1972). Conceptual Dependency: {A} Theory of Natural Language Understanding, Cognitive Psychology, (3)4, 532-631 (see also this shorter summary)
Schank, R. C. and Abelson, R. P. (1977) Scripts, Plans, Goals and Understanding: an Inquiry into Human Knowledge Structures (Chap. 1-3), L. Erlbaum, Hillsdale, NJ (see also this shorter summary)
Schneider, W. & R. M. Shiffrin. (1977). Controlled and automatic human information processing: 1. Detection, search, and attention. Psychological Review, 84, pp1-66.
Schockaert, S. & De Cock, M. (2007). Reasoning about vague topological information. Proceedings of the ACM Conference on Information and Knowledge Management, 593-602.
Schon, D. A. & Wiggins, G. (1992). Kinds of seeing and their functions in designing. Design Studies. 13:2 135--156.
Schrager, J. (1990). Commonsense perception and the psychology of theory formation. In Shrager, J. & Langley, P. (Eds.) Computational Models of Scientific Discovery and Theory Formation. Morgan Kaufman, San Mateo, CA. 437--470.
Schutlz, R., Musa, D., Staszewski, J., & Siegler, R. S. (1994). The relationship between age and major league baseball performance: Implications for development. Psychology and Aging, 9, 274-286.
Schwartz, D. L. & Black, J. B. (1996) Shuttling between depictive models and abstract rules: Induction and fallback. Cognitive Science. 20. 457--497.
Shermer, M. (2011) The Believing Brain. Times Books: New York
Simmons, R., Makatchev, M., Kirby R,. Lee, M., Fanaswala, I., Browning, B., Forlizzi, J. & Sakr, M. (2011). Believable Robot Characters. AI Magazine, winter 2011, 39-52.
Herbert A. Simon (1969).The Sciences of the Artificial (First Edition), MIT Press. Cambridge, MA (a shorter summary)
Simon H.A. (1995). Explaining the Ineffable: AI on the Topics of Intuition, Insight and Inspiration. Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence, 1, 939-948.
Simonton, D. K. (1997). Creative productivity: A predictive and explanatory model of career trajectories and landmarks. Psychological Review, 104, 66-89.
Slezak, P. (1991). Can images be rotated and inspected? A test of the pictorial medium theory. In the Proceedings of the Thirteenth Annual Conference of the Cognitive Science Society (pp. 55-60). Hillsdale, NJ: Erlbaum
Sloman, A. (1995) A Philosophical Encounter. Proceedings of 14th International Joint Conference on Artificial Intelligence. 2037--2040.
de Sousa, R. (2004). Is art an adaptation? prospects for an evolutionary perspective on beauty. Aesthetics and Art Criticism, 62(2), 109-118.
Sperling, G. (1960). The information available in brief visual presentations. Psychological Monographs, 74 1-29.
Stanley, K. Miikkulaine, R. (2004). Competitive Coevolution through Evolutionary Complexification. Journal of Artificial Intelligence Research, 21, 63-100.
M. Stefik, Planning and Meta-Planning (MOLGEN: Part 2). Artificial Intelligence 16 (2), 1981. (see also this structured outline and this other other structured outline)
Sun, R., Coward, L. A., & Zenzen, M. J. (2005). On levels of cognitive modelling. Philosophical Psychology, 18, 613-637.
Tabachneck-Schijf, H. J., Leonardo, A. M., Simon, H. A. (1997). CaMeRa: Computational Model of Multiple Representations. Cognitive Science, 22 (3), 305-350.
Tarr, M. J. (1994). Visual representation: From features to objects. in V. S. Ramachandran (Ed.) Encyclopedia of Human Behavior. San Diego, CA: Academic Press, Vol. 4, 503--512.
Tarr, M. J. & Black, M. J. (1994). A computational and evolutionary perspective on the role of representation in vision. CVGIP: Image Understanding 60(1) 65--73.
Thagard, P. & Hardy, S. (1992) Visual thinking and the development of Dalton's atomic theory. Proceedings of the Ninth Canadian Conference on Artificial Intelligence. Vancouver. 30--37.
P.H. Winston (1980). Learning and Reasoning by Analogy, Communications of the ACM, (23) 12, December 1980
Thomas, N. J. T. (1999). Are theories of imagery theories of imagination? An active perception approach to conscious mental content. Cognitive Science 23, 207--245.
Thomaz, A. L., & Breazeal, C. (2008). Teachable robots: Understanding human teaching behavior to build more effective robot learners. Artificial Intelligence, 172, (6-7), 716-737.
Tijerino, Y.A., Abe, S., and Kishino, F. (1995). Intuitive graphic representation of mental images in a virtual environment through natural language. Computational Models for Integrating Language and Vision, AAAI-95 Fall Symposium Series Working Notes, 29-36.
Treisman, A., Vieira, A., & Hayes, A. (1992). Automatic and preattentive processing. American Journal of Psychology, 105, 341-362.
Trickett, S., Trafton, J., & Schunn, C. (2009). How do scientists respond to anomalies? different strategies used in basic and applied science. Topics in Cognitive Science, 1(4), 711--729.
Valiant, L. G. (1984). A theory of the learnable. Communications of the ACM 1984 pp1134-1142.
Tony Veale & Mark T. Keane: Conceptual Scaffolding: A Spatially Founded Meaning Representation for Metaphor Comprehension. Computational Intelligence 8: 494-519 (1992)
M. M. Veloso. (1994) PRODIGY/ANALOGY: Analogical Reasoning in General Problem Solving. In: S. Wess, K. D. Altho, M. M. Richter (eds). Topics on Case-Based Reasoning, Selected Papers from the First European Workshop on Case-Based Reasoning|EWCBR'93, Vol. 837 of Lecture Notes in Articial Intelligence, Springer-Verlag, pp. 33-50.
Veloso, M.M. & Carbonell, J.G.(1993). Derivational Analogy in PRODIGY: Automating Case Acquisition, Storage, and Utilization. Machine Learning, 10(3):249-278.
Vernon, D., Metta, G. & Sandini, G. (2007). A Survey of artificial cognitive systems: Implications for the autonomous development of mental capabilities in computational agents. IEEE Transactions on evolutionary computation, 11(2), 151-180.
Vincent, A. (2003). Using background knowledge in case-based legal reasoning: A computational model and an intelligent learning environment. Artificial Intelligence, 150, Issue: 1-2, 183-237.
Vogt, Paul. (2005). Meaning development versus predefined meanings in language evolution models. International Joint Conference on Artificial Intelligence. 05, 1154-1161.
von Ahn, L., Liu, R., Blum M. (2006). Peekaboom: A Game for Locating Objects in Images. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 55-64.
Wanderson, A. H. and Hallman, W. K. (1993). Are people acting irrationally? Understanding public concerns about environmental threats. American Psychologist, 48(6), 681--686.
Wang, P. (2007). Three Fundamental Misconceptions of Artificial Intelligence. Journal of Experimental & Theoretical Artificial Intelligence, 19, 249–268.
Warren, R.M. (1970). Restoration of missing speech sounds. Science, 167, 392--393.
D.S. Weld (1994). An Introduction to Least-Commitment Planning, AI Magazine, 15(4):27-61.
Wilensky, Robert (1980). Meta-Planning: Representing and Using Knowledge About Planning in Problem Solving and Natural Language Understanding.
P. Winston, Learning Structural Descriptions from Examples. The Psychology of Computer Vision, P. Winston (ed.), 1975.
Winston, P. H. (1992). Artificial Intelligence. Third Addition. Addison-Wesley.
Woods, W. (1975), What's in a Link: Foundations for Semantic Networks, in D.G. Bobrow & A. Collins (eds.), Representation and Understanding, Academic Press; reprinted in, Collins & Smith (eds.), Readings in Cognitive Science, section 2.2. (see also this shorter summary)
Worden, R. (1998) The evolution of language from social intelligence. to be published in The Evolution of Phonology and Syntax, Hurford, Studdert-Kennedy & Knight (eds) Cambridge University Press. pp148-166.
Zurif, Edgar B. (1990). Language and the brain. In Language: An invitation to Cognitive Science, Vol 1. Osherson, D. N. & Lasnik, H. MIT Press, Cambridge, MA. (pp 177-198)
Zwaan, R. A., Madden, C. J., Yaxley, R. H., & Aveyard, M. E. (2004). Moving words: dynamic reprensentations in language comprehension. Cognitive Science, 28, 611-619.