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Optimism for the future of unified theories

Published online by Cambridge University Press:  12 April 2004

John R. Anderson  and
Christian Lebiere
John R. Anderson*
Affiliation:
Department of Psychology, Carnegie Mellon University, Pittsburgh, Pa 15213
Christian Lebiere*
Affiliation:
Department of Psychology, Carnegie Mellon University, Pittsburgh, Pa 15213
*
ja@cmu.edu
cl@andrew.cmu.edu
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Abstract:

The commentaries on our article encourage us to believe that researchers are beginning to take seriously the goal of achieving the broad adequacy that Newell aspired to. The commentators offer useful elaborations to the criteria we suggested for the Newell Test. We agree with many of the commentators that classical connectionism is too restrictive to achieve this broad adequacy, and that other connectionist approaches are not so limited and can deal with the symbolic components of thought. All these approaches, including ACT-R, need to accept the idea that progress in science is a matter of better approximating these goals, and it is premature to be making judgments of true or false.

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Authors' Response
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Behavioral and Brain Sciences , Volume 26 , Issue 5 , October 2003 , pp. 628 - 639
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Copyright © Cambridge University Press 2003

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References

Ackley, D. H., Hinton, G. E. & Sejnowsky, T. J. (1985) A learning algorithm for Boltzmann machines. Cognitive Science 9:147–69. [aJRA]Google Scholar
Agassi, J. (1987) The wisdom of the eye. Journal of Social and Biological Structures 10:408–13. [JA]10.1016/0140-1750(87)90064-9CrossRefGoogle Scholar
Agassi, J. (1988/2003) Winter 1988 Daedalus. SIGArt Newsletter 105:15–22; reprinted in Agassi (2003). [JA]Google Scholar
Agassi, J. (1992) Heuristic computer-assisted, not computerized: Comments on Simon's project. Journal of Epistemological and Social Studies on Science and Technology 6:15–18. [JA]Google Scholar
Agassi, J. (2003) Science and culture. Boston Studies in the Philosophy of Science, vol. 231. [JA]Google Scholar
Agassi, J. & Laor, N. (2000) How ignoring repeatability leads to magic. Philosophy of the Social Sciences 30:528–86. [JA]10.1177/004839310003000403CrossRefGoogle Scholar
Albright, A. & Hayes, B. (2001) Rules vs. analogy in English past tenses: A computational/experimental study. Department of Linguistics, UCLA. [JLM]Google Scholar
Altmann, E. M. (2002) Functional decay of memory for tasks. Psychological Research 66:287–97. [WDG]10.1007/s00426-002-0102-9CrossRefGoogle ScholarPubMed
Altmann, E. M. & Gray, W. D. (2000) An integrated model of set shifting and maintenance. In: Proceedings of the third international conference on cognitive modeling, pp. 17–24, ed. Taatgen, N. & Aasman, J. Universal Press. [EMA]Google Scholar
Altmann, E. M. & Gray, W. D. (2002) Forgetting to remember: The functional relationship of decay and interference. Psychological Science 13(1):27–33. [WDG]CrossRefGoogle ScholarPubMed
Altmann, E. M. & Trafton, J. G. (2002) Memory for goals: An activation-based model. Cognitive Science 26:39–83. [aJRA]Google Scholar
Anderson, J. R. (1974) Retrieval of propositional information from long-term memory. Cognitive Psychology 5:451–74. [rJRA]10.1016/0010-0285(74)90021-8CrossRefGoogle Scholar
Anderson, J. R. (1976) Language, memory, and thought. Erlbaum. [aJRA]Google Scholar
Anderson, J. R. (1983) The architecture of cognition. Harvard University Press. [arJRA]Google Scholar
Anderson, J. R. (1990) The adaptive character of thought. Erlbaum. [arJRA]Google Scholar
Anderson, J. R. (1991) Is human cognition adaptive? Behavioral and Brain Sciences 14:471–84. [aJRA]10.1017/S0140525X00070801CrossRefGoogle Scholar
Anderson, J. R. (1993) Rules of the mind. Erlbaum. [aJRA, PAMG]Google Scholar
Anderson, J. R. (2000) Learning and memory, 2nd edition. Wiley. [aJRA]Google Scholar
Anderson, J. R. & Betz, J. (2001) A hybrid model of categorization. Psychonomic Bulletin and Review 8:629–47. [aJRA]10.3758/BF03196200CrossRefGoogle ScholarPubMed
Anderson, J. R., Bothell, D., Lebiere, C. & Matessa, M. (1998a) An integrated theory of list memory. Journal of Memory and Language 38:341–80. [aJRA]10.1006/jmla.1997.2553CrossRefGoogle Scholar
Anderson, J. R., Boyle, C. F., Corbett, A. T. & Lewis, M. W. (1990) Cognitive modeling and intelligent tutoring. In: Artificial intelligence and learning environments, ed. Clancey, W. J. & Soloway, E. Elsevier. [WJC]Google Scholar
Anderson, J. R., Budiu, R. & Reder, L. M. (2001) A theory of sentence memory as part of a general theory of memory. Journal of Memory and Language 45:337–67. [aJRA]10.1006/jmla.2000.2770CrossRefGoogle Scholar
Anderson, J. R., Corbett, A. T., Koedinger, K. & Pelletier, R. (1995) Cognitive tutors: Lessons learned. The Journal of Learning Sciences 4:167–207. [rJRA]10.1207/s15327809jls0402_2CrossRefGoogle Scholar
Anderson, J. R. & Douglass, S. (2001) Tower of Hanoi: Evidence for the cost of goal retrieval. Journal of Experimental Psychology: Learning, Memory, and Cognition 27:1331–46. [aJRA]Google Scholar
Anderson, J. R. & Lebiere, C. (1998) The atomic components of thought. Erlbaum. [aJRA, PAMG]Google Scholar
Anderson, J. R., Lebiere, C., Lovett, M. C. & Reder, L. M. (1998b) ACT-R: A higher-level account of processing capacity. Behavioral and Brain Sciences 21:831–32. [aJRA]10.1017/S0140525X98221765CrossRefGoogle Scholar
Anderson, J. R., Qin, Y., Sohn, M-H., Stenger, V. A. & Carter, C. S. (2003) An information-processing model of the BOLD response in symbol manipulation tasks. Psychonomic Bulletin and Review 10:241–61. [arJRA]10.3758/BF03196490CrossRefGoogle ScholarPubMed
Anderson, J. R. & Reder, L. M. (1999a) The fan effect: New results and new theories. Journal of Experimental Psychology: General 128:186–97. [aJRA]10.1037/0096-3445.128.2.186CrossRefGoogle Scholar
Anderson, J. R. & Reder, L. M. (1999b) The size of the fan effect: Process not representation. Journal of Experimental Psychology: General 128:207–10. [rJRA]10.1037/0096-3445.128.2.207CrossRefGoogle Scholar
Asher, N., Aurnague, M., Bras, M., Sblayrolles, P. & Vieu., L. (1994) Computing the spatiotemporal structure of discourse. 1st International Workshop on Computational Semantics, Dept. of Computational Linguistics, University of Tilburg, NL. [AGBtM]Google Scholar
Atran, S. (2002) Modes of adaptationism: Muddling through cognition and language. Commentary on Andrews et al. Behavioral and Brain Sciences 25(4):504–506. [IP]10.1017/S0140525X02220099CrossRefGoogle Scholar
Baddeley, A. D. (1986) Working memory. Oxford University Press. [aJRA]Google ScholarPubMed
Ballard, D. H., Hayhoe, M. M., Pook, P. K. & Rao, R. P. N. (1997) Deictic codes for the embodiment of cognition. Behavioral and Brain Sciences 20(4):723–42. [WDG]10.1017/S0140525X97001611CrossRefGoogle ScholarPubMed
Baron-Cohen, S. (1996) Can children with autism integrate first and third person representations? Behavioral and Brain Sciences 19(1):123–24. [WJC]10.1017/S0140525X00041819CrossRefGoogle Scholar
Barresi, J. & Moore, C. (1996) Intentional relations and social understanding. Behavioral and Brain Sciences 19(1)107–54. [WJC]10.1017/S0140525X00041790CrossRefGoogle Scholar
Barrett, J. L. (1998) Cognitive constraints on Hindu concepts of the divine. Journal for the Scientific Study of Religion 37:608–19. [IP]10.2307/1388144CrossRefGoogle Scholar
Barrett, J. L. (1999) Theological correctness: Cognitive constraint and the study of religion. Method and Theory in the Study of Religion 11:325–39. [IP]10.1163/157006899X00078CrossRefGoogle Scholar
Barrett, J. L. & Keil, F. E. (1996) Conceptualizing a nonnatural entity: Anthropomorphism in God concepts. Cognitive Psychology 31:219–47. [IP]10.1006/cogp.1996.0017CrossRefGoogle ScholarPubMed
Barwise, J. (1980) Infinitary logics. In: Modern logic: A survey, ed. Agazzi, E. Reidel. [YY]Google Scholar
Besner, D., Twilley, L., McCann, R. S. & Seergobin, K. (1990) On the connection between connectionism and data: Are a few words necessary? Psychological Review 97(3):432–46. [JLM]10.1037/0033-295X.97.3.432CrossRefGoogle Scholar
Bever, T. G., Fodor, J. A. & Garret, M. (1968) A formal limitation of association. In: Verbal behavior and general behavior theory, ed. Dixon, T. R. & Horton, D. L. Prentice Hall. [aJRA]Google Scholar
Bird, H., Lambon Ralph, M. A., Seidenberg, M. S., McClelland, J. L. & Patterson, K. (2003) Deficits in phonology and past-tense morphology: What's the connection? Neuropsychologia 48:502–26. [JLM]Google Scholar
Block, N. (1995) On a confusion about a function of consciousness. Behavioral and Brain Sciences 18:227–87. [rJRA, MO, YY]10.1017/S0140525X00038188CrossRefGoogle Scholar
Boardman, I., Grossberg, S., Myers, C. & Cohen, M. (1999) Neural dynamics of perceptual order and context effects for variable-rate speech syllables. Perception and Psychophysics 61:1477–1500. [SG]10.3758/BF03213112CrossRefGoogle ScholarPubMed
Bock, K. (1986) Syntactic persistence in language production. Cognitive Psychology 18:355–87. [aJRA]10.1016/0010-0285(86)90004-6CrossRefGoogle Scholar
Bock, K. & Griffin, Z. M. (2000) The persistence of structural priming: Transient activation or implicit learning? Journal of Experimental psychology: General 129:177–92. [aJRA]10.1037/0096-3445.129.2.177CrossRefGoogle ScholarPubMed
Boolos, G. & Jeffrey, R. (1989) Computability and logic. Cambridge University Press. [YY]Google Scholar
Botvinick, M. & Plaut, D. C. (in press) Doing without schema hierarchies: A recurrent connectionist approach to normal and impaired routine sequential action. Psychological Review. [aJRA]Google Scholar
Bouvet, S. (2001) Learning an ideal strategy in tic-tac-toe with DAC5. Technical Report: Institute of Neuroinformatics 2001–12. [PFMJV]Google Scholar
Boyer, P. (2001) Religion explained: The evolutionary origins of religious thought. Basic Books. [IP]Google Scholar
Bradski, G., Carpenter, G. A. & Grossberg, S. (1994) STORE working memory networks for storage and recall of arbitrary temporal sequences. Biological Cybernetics 71:469–80. [SG]10.1007/BF00198465CrossRefGoogle Scholar
Bringsjord, S. (2000) Animals, zombanimals, and the total Turing Test: The essence of artificial intelligence. Journal of Logic, Language, and Information 9:397–418. [YY]10.1023/A:1008311207953CrossRefGoogle Scholar
Bringsjord, S. (2001) Are we evolved computers?: A critical review of Steven Pinker's How the mind works. Philosophical Psychology 14(2):227–43. [IP]Google Scholar
Bringsjord, S. & Zenzen, M. (2003) Superminds: People harness hypercomputation, and more. Kluwer. [YY]10.1007/978-94-010-0283-7CrossRefGoogle Scholar
Brown, J., Bullock, D. & Grossberg, S. (1999) How the basal ganglia use parallel excitatory and inhibitory learning pathways to selectively respond to unexpected rewarding cues. Journal of Neuroscience 19:10502–511. [SG]10.1523/JNEUROSCI.19-23-10502.1999CrossRefGoogle ScholarPubMed
Brown, R. (1973) A first language. Harvard University Press. [aJRA,JLM]10.4159/harvard.9780674732469CrossRefGoogle Scholar
Browne, A. & Sun, R. (2001) Connectionist inference models. Neural Networks 14:1331–55. [aJRA]10.1016/S0893-6080(01)00109-5CrossRefGoogle ScholarPubMed
Budiu, R. (2001) The role of background knowledge in sentence processing. Doctoral dissertation, Carnegie Mellon University, Pittsburgh, PA. [aJRA]Google Scholar
Budiu, R. & Anderson, J. R. (in press) Interpretation-based processing: A unified theory of semantic processing. Cognitive Science. [aJRA]Google Scholar
Bullock, D., Cisek, P. & Grossberg, S. (1998) Cortical networks for control of voluntary arm movements under variable force conditions. Cerebral Cortex 8:48–62. [SG]10.1093/cercor/8.1.48CrossRefGoogle ScholarPubMed
Bullock, D., Grossberg, S. & Guenther, F. (1993a) A self-organizing neural model of motor equivalent reaching and tool use by a multijoint arm. Journal of Cognitive Neuroscience 5:408–35. [SG]10.1162/jocn.1993.5.4.408CrossRefGoogle Scholar
Bullock, D., Grossberg, S. & Mannes, C. (1993b) A neural network model for cursive script production. Biological Cybernetics 70:15–28. [SG]10.1007/BF00202562CrossRefGoogle Scholar
Bunge, M. (1980) The mind-body problem: A psychobiological approach. Pergamon Press. [PAMG]Google Scholar
Burzio, L. (1999) Missing players: Phonology and the past-tense debate. Unpublished manuscript. Johns Hopkins University, Baltimore, MD. [aJRA]Google Scholar
Bybee, J. L. (1995) Regular morphology and the lexicon. Language and Cognitive Processes 10:425–55. [JLM]10.1080/01690969508407111CrossRefGoogle Scholar
Byrne, M. D. & Anderson, J. R. (1998) Perception and action. In: The atomic components of thought, ed. Anderson, J. R. & Lebiere, C. Erlbaum. [aJRA]Google Scholar
Byrne, M. D. & Anderson, J. R. (2001) Serial modules in parallel: The psychological refractory period and perfect time-sharing. Psychological Review 108:847–69. [aJRA]10.1037/0033-295X.108.4.847CrossRefGoogle ScholarPubMed
Callan, D. E., Kent, R. D., Guenther, F. H. & Vorperian, H. K. (2000) An auditoryfeedback-based neural network model of speech production that is robust to developmental changes in the size and shape of the articulatory system. Journal of Speech, Language, and Hearing Research 43:721–36. [SG]10.1044/jslhr.4303.721CrossRefGoogle ScholarPubMed
Calvo, F. & Colunga, E. (2003) The statistical brain: Reply to Marcus’ The algebraic mind. In: Proceedings of the Twenty-Fifth Annual Conference of the Cognitive Science Society, ed. Alterman, R. & Kirsh, D. Erlbaum. [FCG]Google Scholar
Calvo, F. & Colunga, E. (in preparation) Transfer of learning in infants: Combined Hebbian and errordriven learning. [FCG]Google Scholar
Carpenter, G. A., Gopal, S., Macomber, S., Martens, S., Woodcock, C. E. & Franklin, J. (1999) A neural network method for efficient vegetation mapping. Remote Sensing of Environment 70:326–38. [SG]10.1016/S0034-4257(99)00051-6CrossRefGoogle Scholar
Carpenter, G. A. & Grossberg, S., eds. (1991) Pattern recognition by selforganizing neural networks. MIT Press. [SG]10.7551/mitpress/5271.001.0001CrossRefGoogle Scholar
Carpenter, G. A., Grossberg, S., Markuzon, N., Reynolds, J. H. & Rosen, D. (1992) Fuzzy ARTMAP: A neural network architecture for incremental supervised learning of analog multidimensional maps. IEEE Transactions on Neural Networks 3(5):698–713. [SG]10.1109/72.159059CrossRefGoogle ScholarPubMed
Carpenter, G. A. & Milenova, B. L. (2000) ART neural networks for medical data analysis and fast distributed learning. In: Artificial neural networks in medicine and biology. Proceedings of the ANNIMAB-1 Conference, Göteborg, Sweden, 13–16 May 2000, ed. Malmgren, H., Borga, M. & Niklasson, L. Springer-Verlag. (Springer series, Perspectives in Neural Computing.) [SG]Google Scholar
Chaiken, S. & Trope, Y., eds. (1999) Dual-process theories in social psychology. Guilford Press. [IP]Google Scholar
Chalmers, D. J. (1996) The conscious mind. Oxford University Press. [MO]Google Scholar
Chase, W. G. & Ericsson, K. A. (1982) Skill and working memory. In: The psychology of learning and motivation, vol. 16, ed Bower, G. H. Academic Press. [aJRA]Google Scholar
Chomsky, N. A. (1965) Aspects of a theory of syntax. MIT Press. [aJRA]Google Scholar
Clancey, W. J. (1999a) Conceptual coordination: How the mind orders experience in time. Erlbaum. [WJC]10.4324/9781410603609CrossRefGoogle Scholar
Clancey, W. J. (1999b) Studying the varieties of consciousness: Stories about zombies or the life about us? Journal of the Learning Sciences 8(3–4):525–40. [WJC]10.1207/s15327809jls0803&4_11CrossRefGoogle Scholar
Clancey, W. J. (2000) Conceptual coordination bridges information processing and neuropsychology. Behavioral and Brain Sciences 23(6):919–22. [WJC]10.1017/S0140525X00334021CrossRefGoogle Scholar
Clark, A. (1997) Being there. MIT Press. [DS]Google Scholar
Clark, A. (1998) The dynamic challenge. Cognitive Science 21(4):461–81. [aJRA]10.1207/s15516709cog2104_3CrossRefGoogle Scholar
Clark, A. (1999) Where brain, body, and world collide. Journal of Cognitive Systems Research 1:5–17. [aJRA]10.1016/S1389-0417(99)00002-9CrossRefGoogle Scholar
Cleeremans, A. (1993) Mechanisms of implicit learning: Connectionist models of sequence processing. MIT Press. [aJRA]10.7551/mitpress/4528.001.0001CrossRefGoogle Scholar
Cohen, J. D. & Schooler, J. W., eds. (1997) Scientific approaches to consciousness: 25th Carnegie Symposium on Cognition. Erlbaum. [aJRA]Google Scholar
Cohen, M. A. & Grossberg, S. (1986) Neural dynamics of speech and language coding: Developmental programs, perceptual grouping, and competition for short-term memory. Human Neurobiology 5:1–22. [SG]Google ScholarPubMed
Collins, M. (1999) Head-driven statistical models for nature language parsing. Doctoral dissertation, University of Pennsylvania. [aJRA]Google Scholar
Coltheart, M., Curtis, B., Atkins, P. & Haller, M. (1993) Models of reading aloud: Dual-route and parallel-distributed-processing approaches. Psychological Review 100(4):589–608. [JLM]10.1037/0033-295X.100.4.589CrossRefGoogle Scholar
Commons, M. L. & Richards, F. A. (2002) Organizing components into combinations: How stage transition works. Journal of Adult Development 9(3):159–77. [MLC]10.1023/A:1016047925527CrossRefGoogle Scholar
Commons, M. L., Trudeau, E. J., Stein, S. A., Richards, F. A. & Krause, S. R. (1998) The existence of developmental stages as shown by the hierarchical complexity of tasks. Developmental Review 8(3):237–78. [MLC]10.1006/drev.1998.0467CrossRefGoogle Scholar
Contreras-Vidal, J. L., Grossberg, S. & Bullock, D. (1997) A neural model of cerebellar learning for arm movement control: Cortico-spino-cerebellar dynamics. Learning and Memory 3:475–502. [SG]10.1101/lm.3.6.475CrossRefGoogle ScholarPubMed
Cosmides, L. & Tooby, J. (2000a) Consider the source: The evolution of adaptations for decoupling and metarepresentation. In: Metarepresentations: A multidisciplinary perspective, ed. Sperber, D. Oxford University Press. [IP]Google Scholar
Cosmides, L. & Tooby, J. (2000b) The cognitive neuroscience of social reasoning. In: The new cognitive neurosciences, 2nd edition, ed. Gazzaniga, M. S. MIT Press. [aJRA]Google Scholar
Dawson, T. L. (2002) A comparison of three developmental stage scoring systems. Journal of Applied Measurement 3(2):146–89. [MLC]Google ScholarPubMed
Denes-Raj, V. & Epstein, S. (1994) Conflict between intuitive and rational processing: When people behave against their better judgment. Journal of Personality and Social Psychology 66(5):819–29. [IP]10.1037/0022-3514.66.5.819CrossRefGoogle ScholarPubMed
Dennett, D. C. (1991) Consciousness explained. Little, Brown. [aJRA]Google Scholar
Dennett, D. C. & Kinsbourne, M. (1995) Time and the observer: The where and when of consciousness in the brain. Behavioral and Brain Sciences 15(2):183–247. [aJRA]10.1017/S0140525X00068229CrossRefGoogle Scholar
Dolan, C. P. & Smolensky, P. (1989) Tensor product production system: A modular architecture and representation. Connection Science 1:53–68. [aJRA]10.1080/09540098908915629CrossRefGoogle Scholar
Edelman, G. M. (1989) The remembered present: A biological theory of consciousness. BasicBooks. [PAMG]Google Scholar
Edelman, G. M. (1992) Bright air, brilliant fire: On the matter of the mind. BasicBooks. [PAMG]Google Scholar
Edelman, G. M. & Tononi, G. (2000) Consciousness: How matter becomes imagination. Penguin Press. [PAMG]Google Scholar
Ehret, B. D., Gray, W. D. & Kirschenbaum, S. S. (2000) Contending with complexity: Developing and using a scaled world in applied cognitive research. Human Factors 42(1):8–23. [WDG]10.1518/001872000779656606CrossRefGoogle ScholarPubMed
Elman, J. L. (1995) Language as a dynamical system. In: Mind as motion: Explorations in the dynamics of cognition, ed. Port, R. F. & Gelder, T. V. MIT Press. [aJRA]Google Scholar
Elman, J. L., Bates, E. A. Johnson, M. H., Karmiloff-Smith, A., Parisi, D. & Plunkett, K. (1996) Rethinking innateness: A connectionist perspective on development. MIT Press. [arJRA, CFO]10.7551/mitpress/5929.001.0001CrossRefGoogle Scholar
Emond, B. (in preparation) ACT-R/WN: Towards an implementation of WordNet in the ACT-R cognitive architecture. [aJRA]Google Scholar
Emond, B. & Ferres, L. (2001) Modeling the false-belief task: An ACT-R implementation of Wimmer and Perner (1983). Paper presented at the Second Bisontine Conference for Conceptual and Linguistic Development in the Child aged from 1 to 6 Years, Besançon, France, March 21–23, 2001. [aJRA]Google Scholar
Eng, K., Klein, D., Bäbler, A., Bernardet, U., Blanchard, U., Costa, M., Delbrück, T., Douglas, R. J., Hepp, K., Manzolli, J., Mintz, M., Roth, F., Rutishauser, U., Wassermann, K., Whatley, A. M., Wittmann, A., Wyss, R., Verschure, P. F. M. J. (2003) Design for a brain revisited: The neuromorphic design and functionality of the interactive space Ada. Reviews in the Neurosciences 1–2:145–80. [PFMJV]Google Scholar
Engel, A. K., Fries, P. & Singer, W. (2001) Dynamic predictions, oscillations and synchrony in top-down processing. Nature Reviews Neuroscience 2:704–16. [SG]10.1038/35094565CrossRefGoogle ScholarPubMed
Epstein, S., Lipson, A., Holstein, C. & Huh, E. (1992) Irrational reactions to negative outcomes: Evidence for two conceptual systems. Journal of Personality and Social Psychology 62(2):328–39. [IP]10.1037/0022-3514.62.2.328CrossRefGoogle ScholarPubMed
Epstein, S. & Pacini, R. (1999) Some basic issues regarding dual-process theories from the perspective of cognitive-experiential self-theory. In: Dual-process theories in social psychology, ed. Chaiken, S. & Trope, Y. Guilford Press. [IP]Google Scholar
Ericsson, K. A. & Kintsch, W. (1995) Long-term working memory. Psychological Review 102:211–45. [aJRA]10.1037/0033-295X.102.2.211CrossRefGoogle ScholarPubMed
Fellbaum, C., ed. (1998) WordNet: An electronic lexical database. MIT Press. [aJRA]10.7551/mitpress/7287.001.0001CrossRefGoogle Scholar
Ferreira, F. & Clifton, C. (1986) The independence of syntactic processing. Journal of Memory and Language 25:348–68. [aJRA]10.1016/0749-596X(86)90006-9CrossRefGoogle Scholar
Fiala, J. C., Grossberg, S. & Bullock, D. (1996) Metabotropic glutamate receptor activation in cerebellar Purkinje cells as substrate for adaptive timing of the classically conditioned eye-blink response. Journal of Neuroscience 16:3760–74. [SG]10.1523/JNEUROSCI.16-11-03760.1996CrossRefGoogle ScholarPubMed
Fincham, J. M., VanVeen, V., Carter, C. S., Stenger, V. A. & Anderson, J. R. (2002) Integrating computational cognitive modeling and neuroimaging: An event-related fMRI study of the Tower of Hanoi task. Proceedings of the National Academy of Science 99:3346–51. [aJRA]10.1073/pnas.052703399CrossRefGoogle Scholar
Fodor, J. A. (1983) The modularity of mind. MIT Press/Bradford Books. [aJRA]10.7551/mitpress/4737.001.0001CrossRefGoogle Scholar
Fodor, J. A. (2000) The mind doesn't work that way. MIT Press. [aJRA]10.7551/mitpress/4627.001.0001CrossRefGoogle Scholar
Frank, M. J., Loughry, B. & O’Reilly, R. C. (2000) Interactions between frontal cortex and basal ganglia in working memory: A computational model. Technical Report (00–01, November), Institute of Cognitive Science, University of Colorado, Boulder, CO. [aJRA]Google Scholar
Gancarz, G. & Grossberg, G. (1999) A neural model of the saccadic eye movement control explains task-specific adaptation. Vision Research 39:3123–43. [SG]10.1016/S0042-6989(99)00049-8CrossRefGoogle ScholarPubMed
Gelepithis, P. A. M. (1984) On the foundations of artificial intelligence and human cognition. Ph. D. thesis, Department of Cybernetics, Brunel University, England. [PAMG]Google Scholar
Gelepithis, P. A. M. (1991) The possibility of machine intelligence and the impossibility of humanmachine communication. Cybernetica 34(4):255–68. [PAMG]Google Scholar
Gelepithis, P. A. M. (1997) A Rudimentary theory of information: Consequences for information science and information systems. World Futures 49:263–74. (Reprinted in: The quest for a unified theory of information, ed. Hofkirchner, W.. Gordon and Breach.) [PAMG]10.1080/02604027.1997.9972635CrossRefGoogle Scholar
Gelepithis, P. A. M. (1999) Embodiments of theories of mind: A review and comparison. In: Computational methods and neural networks, ed. Bekakos, M. P., Sambandham, M. & Evans, D. J. Dynamic. [PAMG]Google Scholar
Gelepithis, P. A. M. (2001) A concise comparison of selected studies of consciousness, Cognitive Systems 5(4):373–92. [PAMG]Google Scholar
Gelepithis, P. A. M. (2002) Computing, dynamics, and the third way. Proceedings of the Second International Conference on Neural, Parallel, and Scientific Computations, 2002, vol. II, pp. 17–21. [PAMG]Google Scholar
Gelepithis, P. A. M. & Goodfellow, R. (1992) An alternative architecture for intelligent tutoring systems: Theoretical and implementational aspects. Interactive Learning International 8(3):171–75. [PAMG]Google Scholar
Gelepithis, P. A. M. & Parillon, N. (2002) Knowledge management: Analysis and some consequences. In: Knowledge management and business process reengineering, ed. Hlupic, V. Idea Book. [PAMG]Google Scholar
Gibson, J. J. (1979) The ecological approach to visual perception. Houghton Mifflin. [MO]Google Scholar
Giere, R. (1998) Explaining science. Chicago University Press. [PAMG]Google Scholar
Gigerenzer, G. (2000) Adaptive thinking: Rationality in the real world. Oxford University Press. [aJRA]Google Scholar
Gopnik, M. & Crago, M. B. (1991) Familial aggregation of a developmental language disorder. Cognition 39:1–50. [JLM]10.1016/0010-0277(91)90058-CCrossRefGoogle ScholarPubMed
Gould, S. J. & Lewontin, R. C. (1979) The Spandrels of San Marco and the Panglossian paradigm: A critique of the adaptationist program. Proceedings of the Royal Society of London 205:581–98. [aJRA]Google Scholar
Granger, E., Rubin, M., Grossberg, S. & Lavoie, P. (2001) A what-and-where fusion neural network for recognition and tracking of multiple radar emitters. Neural Networks 14:325–44. [SG]10.1016/S0893-6080(01)00019-3CrossRefGoogle ScholarPubMed
Gray, W. D. & Boehm-Davis, D. A. (2000) Milliseconds matter: An introduction to microstrategies and to their use in describing and predicting interactive behavior. Journal of Experimental Psychology: Applied 6(4):322–35. [WDG]Google ScholarPubMed
Gray, W. D., John, B. E. & Atwood, M. E. (1993) Project Ernestine: Validating a GOMS analysis for predicting and explaining real-world performance. Human-Computer Interaction 8(3):237–309. [WDG]10.1207/s15327051hci0803_3CrossRefGoogle Scholar
Gray, W. D., Schoelles, M. J. & Fu, W.-T. (2000) Modeling a continuous dynamic task. In: Third International Conference on Cognitive Modeling, ed. Taatgen, N. & Aasman, J. Universal Press. [WDG]Google Scholar
Gray, W. D., Schoelles, M. J. & Myers, C. W. (2002) Computational cognitive models ISO ecologically optimal strategies. In: 46th Annual Conference of the Human Factors and Ergonomics Society, pp. 492–96. Human Factors and Ergonomics Society. [WDG]Google Scholar
Green, C. D. (1998) Are connectionist models theories of cognition? Psycoloquy 9(04). http://www.cogsci.ecs.soton.ac.uk/cgi/psyc/newpsy?9.04. [PNP]Google Scholar
Greeno, J. G. (1989) Situations, mental models and generative knowledge. In: Complex information processing: The impact of Herbert A. Simon, ed. Klahr, D. & Kotovsky, K. Erlbaum. [aJRA]Google Scholar
Grossberg, S. (1976) Adaptive pattern classification and universal recoding, II: Feedback, expectation, olfaction, and illusions. Biological Cybernetics 23:187–202. [SG]10.1007/BF00340335CrossRefGoogle ScholarPubMed
Grossberg, S. (1978a) A theory of human memory: Self-organization and performance of sensory-motor codes, maps, and plans. In: Progress in theoretical biology, vol. 5, ed. Rosen, R. & Snell, F. Academic Press. [SG]Google Scholar
Grossberg, S. (1978b) Behavioral contrast in short-term memory: Serial binary memory models or parallel continuous memory models? Journal of Mathematical Psychology 3:199–219. [SG]10.1016/0022-2496(78)90016-0CrossRefGoogle Scholar
Grossberg, S. (1980) How does a brain build a cognitive code? Psychological Review 87:1–51. [SG]10.1037/0033-295X.87.1.1CrossRefGoogle ScholarPubMed
Grossberg, S. (1988) Nonlinear neural networks: Principles, mechanisms, and architectures. Neural Networks 1:17–61. [SG]10.1016/0893-6080(88)90021-4CrossRefGoogle Scholar
Grossberg, S. (1999a) How does the cerebral cortex work? Learning, attention, and grouping by the laminar circuits of visual cortex. Spatial Vision 12:163–86. [SG]10.1163/156856899X00102CrossRefGoogle Scholar
Grossberg, S. (1999b) The link between brain learning, attention, and consciousness. Consciousness and Cognition 8:1–44. [SG]10.1006/ccog.1998.0372CrossRefGoogle Scholar
Grossberg, S. (2000a) How hallucinations may arise from brain mechanisms of learning, attention, and volition. Journal of the International Neuropsychological Society 6:583–92. [SG]10.1017/S135561770065508XCrossRefGoogle Scholar
Grossberg, S. (2000b) The complementary brain: Unifying brain dynamics and modularity. Trends in Cognitive Sciences 4:233–46. [SG]10.1016/S1364-6613(00)01464-9CrossRefGoogle Scholar
Grossberg, S. (2000c) The imbalanced brain: From normal behavior to schizophrenia. Biological Psychiatry 48:81–98. [SG]10.1016/S0006-3223(00)00903-3CrossRefGoogle Scholar
Grossberg, S., Boardman, I. & Cohen, C. (1997a) Neural dynamics of variable-rate speech categorization. Journal of Experimental Psychology: Human Perception and Performance 23:418–503. [SG]Google Scholar
Grossberg, S. & Kuperstein, M. (1989) Neural dynamics of adaptive sensory-motor control: Expanded edition. Pergamon Press. [SG]Google Scholar
Grossberg, S. & Merrill, J. W. L. (l992) A neural network model of adaptively timed reinforcement learning and hippocampal dynamics. Cognitive Brain Research 1:3–38. [SG]CrossRefGoogle Scholar
Grossberg, S. & Merrill, J. W. L. (l996) The hippocampus and cerebellum in adaptively timed learning, recognition, and movement. Journal of Cognitive Neuroscience 8:257–77. [SG]10.1162/jocn.1996.8.3.257CrossRefGoogle Scholar
Grossberg, S. & Myers, C. W. (2000) The resonant dynamics of speech perception: Interword integration and duration-dependent backward effects. Psychological Review 107:735–67. [SG]10.1037/0033-295X.107.4.735CrossRefGoogle ScholarPubMed
Grossberg, S. & Paine, R. W. (2000) A neural model of corticocerebellar interactions during attentive imitation and predictive learning of sequential handwriting movements. Neural Networks 13:999–1046. [SG]10.1016/S0893-6080(00)00065-4CrossRefGoogle ScholarPubMed
Grossberg, S., Roberts, K., Aguilar, M. & Bullock, D. (1997b) A neural model of multimodal adaptive saccadic eye movement control by superior colliculus. Journal of Neuroscience 17:9706–25. [SG]10.1523/JNEUROSCI.17-24-09706.1997CrossRefGoogle Scholar
Grossberg, S. & Stone, G. O. (1986a) Neural dynamics of attention switching and temporal order information in short-term memory. Memory and Cognition 14:451–68. [SG]10.3758/BF03202517CrossRefGoogle Scholar
Grossberg, S. & Stone, G. O. (1986b) Neural dynamics of word recognition and recall: Attentional priming, learning, and resonance. Psychological Review 93:46–74. [SG]10.1037/0033-295X.93.1.46CrossRefGoogle Scholar
Guenther, F. H. (1995) Speech sound acquisition, coarticulation, and rate effects in a neural network model of speech production. Psychological Review 102:594–621. [SG]10.1037/0033-295X.102.3.594CrossRefGoogle Scholar
Hahn, U. & Nakisa, R. C. (2000) German inflection: Single-route or dual-route? Cognitive Psychology 41:313–60. [JLM]10.1006/cogp.2000.0737CrossRefGoogle ScholarPubMed
Hameroff, S. R., Kaszniak, A. W. & Scott, A. C., eds. (1998) Toward a science of consciousness II: The second Tucson discussions and debates. MIT Press. [PAMG]Google Scholar
Harnad, S. (1990) The symbol grounding problem. Physica D 42:335–46. [aJRA]10.1016/0167-2789(90)90087-6CrossRefGoogle Scholar
Harnad, S. (1994) Computation is just interpretable symbol manipulation; Cognition isn’t. Minds and Machines 4:379–90. [aJRA]10.1007/BF00974165CrossRefGoogle Scholar
Hartley, R. F. (2000) Cognition and the computational power of connectionist networks. Connection Science 12(2):95–110. [aJRA]Google Scholar
Hartley, R. & Szu, H. (1987) A comparison of the computational power of neural network models. Proceedings of the First International Conference on Neural Networks 3:15–22. [aJRA]Google Scholar
Haverty, L. A., Koedinger, K. R., Klahr, D. & Alibali, M. W. (2000) Solving induction problems in mathematics: Not-so-trivial pursuit. Cognitive Science 24(2):249–98. [aJRA]Google Scholar
Hebb, D. O. (1949) The organization of behavior. Wiley. [PAMG]Google Scholar
Hinrichs, E. (1986) Temporal anaphora in discourses of English. Linguistics and Philosophy 9:63–82. [AGBtM]10.1007/BF00627435CrossRefGoogle Scholar
Hinton, G. E. & Sejnowsky, T. J. (1986) Learning and relearning in Boltzmann machines. In: Parallel distributed processing: Explorations in the microstructure of cognition, vol. 1: Foundations, ed. Rumelhart, D. E., McClelland, J. L. & The PDP Group. MIT Press. [aJRA]Google Scholar
Hoeffner, J. H. (1996) A single mechanism account of the acquisition and processing of regular and irregular inflectional morphology. Unpublished doctoral dissertation, Department of Psychology, Carnegie Mellon University, Pittsburgh, PA. [JLM]Google Scholar
Hofstötter, C., Mintz, M. & Verschure, P. F. M. J. (2002) The cerebellum in action: A simulation and robotics study. European Journal of Neuroscience 16:1361–76. [PFMJV]10.1046/j.1460-9568.2002.02182.xCrossRefGoogle Scholar
Holyoak, K. J. & Spellman, B. A. (1993) Thinking. Annual Review of Psychology 44:265–315. [IP]10.1146/annurev.ps.44.020193.001405CrossRefGoogle Scholar
Hopfield, J. J. (1982) Neural networks and physical systems with emergent collective computational abilities. Proceedings of the National Academy of Sciences USA 79:2554–58. [aJRA]10.1073/pnas.79.8.2554CrossRefGoogle ScholarPubMed
Hornik, K., Stinchcombe, M. & White, H. (1989) Multilayer feed forward networks are universal approximators. Neural Computation 2:210–15. [aJRA]Google Scholar
Howes, A. & Young, R. M. (1997) The role of cognitive architecture in modelling the user: SOAR's learning mechanism. Human-Computer Interaction 12:311–43. [RMY]10.1207/s15327051hci1204_2CrossRefGoogle Scholar
Hummel, J. E. & Holyoak, K. J. (1998) Distributed representations of structure. A theory of analogical access and mapping. Psychological Review 104:427–66. [aJRA]10.1037/0033-295X.104.3.427CrossRefGoogle Scholar
Hutchins, E. (1995) Cognition in the wild. MIT Press. [DS]10.7551/mitpress/1881.001.0001CrossRefGoogle Scholar
Joanisse, M. F. & Seidenberg, M. S. (1999) Impairments in verb morphology following brain injury: A connectionist model. Proceedings of the National Academy of Sciences 96:7592–97. [JLM]10.1073/pnas.96.13.7592CrossRefGoogle Scholar
Johnson, M. H., Munakata, Y. & Gilmore, R. O., eds. (2002) Brain development and cognition: A reader. Blackwell. [PAMG]Google Scholar
Jones, G., Ritter, F. E. & Wood, D. J. (2000) Using a cognitive architecture to examine what develops. Psychological Science 11(2):1–8. [aJRA]10.1111/1467-9280.00222CrossRefGoogle ScholarPubMed
Jones, R. M., Laird, J. E., Nielsen, P. E., Coulter, K. J., Kenny, P. & Koss, F. V. (1999) Automated intelligent pilots for combat flight simulation. AI Magazine 20:27–41. [aJRA]Google Scholar
Jongman, L. & Taatgen, N. A. (1999) An ACT-R model of individual differences in changes in adaptivity due to mental fatigue. In: Proceedings of the 21st Annual Conference of the Cognitive Science Society. Erlbaum. [aJRA]Google Scholar
Kandel, E. R. & O’Dell, T. J. (1992) Are adult learning mechanisms also used for development? Science 258:243–45. [SG]10.1126/science.1411522CrossRefGoogle ScholarPubMed
Karmiloff-Smith, A. (1992) Beyond modularity: A developmental perspective on cognitive science. MIT Press. [CFO]10.7551/mitpress/1579.001.0001CrossRefGoogle Scholar
Karmiloff-Smith, A. (1997) Crucial differences between developmental cognitive neuroscience and adult neuropsychology. Developmental Neuropsychology 13(4):513–24. [CFO]10.1080/87565649709540693CrossRefGoogle Scholar
Karmiloff-Smith, A. (1998) Development itself is the key to understanding developmental disorders. Trends in Cognitive Sciences 2(10):389–98. [CFO]10.1016/S1364-6613(98)01230-3CrossRefGoogle Scholar
Karmiloff-Smith, A., Plunkett, K., Johnson, M. H., Elman, J. L. & Bates, E. A. (1998) What does it mean to claim that something is “innate”? Mind and Language 13(4):588–97. [CFO]10.1111/1468-0017.00095CrossRefGoogle Scholar
Karmiloff-Smith, A., Scerif, G. & Ansari, D. (2003) Double dissociations in developmental disorders? Theoretically misconceived, empirically dubious. Cortex 39:161–63. [CFO]10.1016/S0010-9452(08)70091-1CrossRefGoogle ScholarPubMed
Karmiloff-Smith, A., Scerif, G. & Thomas, M. S. C. (2002) Different approaches to relating genotype to phenotype in developmental disorders. Developmental Psychobiology 40:311–22. [CFO]10.1002/dev.10035CrossRefGoogle ScholarPubMed
Kilgard, M. P. & Merzenich, M. M. (1998) Cortical map reorganization enabled by nucleus basalis activity. Science 279:1714–18. [PFMJV]10.1126/science.279.5357.1714CrossRefGoogle ScholarPubMed
Kimberg, D. Y. & Farah, M. J. (1993) A unified account of cognitive impairments following frontal lobe damage: The role of working memory in complex, organized behavior. Journal of Experimental Psychology: General 122:411–28. [aJRA]10.1037/0096-3445.122.4.411CrossRefGoogle ScholarPubMed
Kirsh, D. & Maglio, P. P. (1994) On distinguishing epistemic from pragmatic action. Cognitive Science 18(4):513–49. [DS]10.1207/s15516709cog1804_1CrossRefGoogle Scholar
Koedinger, K. R., Anderson, J. R., Hadley, W. H. & Mark, M. (1997) Intelligent tutoring goes to school in the big city. International Journal of Artificial Intelligence in Education 8:30–43. [rJRA]Google Scholar
Laird, J. E. (1986) Universal subgoaling. In: Universal subgoaling and chunking: The automatic generation and learning of goal hierarchies, ed. Laird, J. E., Rosenbloom, P. S. & Newell, A. Kluwer. [RMY]10.1007/978-1-4613-2277-1CrossRefGoogle Scholar
Lakatos, I. (1970) Falsification and the methodology of scientific research programmes. In: Criticism and the growth of knowledge, ed. Lakatos, I. & Musgrave, A. Cambridge University Press. [CFO]10.1017/CBO9781139171434CrossRefGoogle Scholar
Langacker, R. W. (1986) An introduction to cognitive grammar. Cognitive Science 10(1):1–40. [WJC]10.1207/s15516709cog1001_1CrossRefGoogle Scholar
Langley, P. (1999) Concrete and abstract models of category learning. In: Proceedings of the 21st Annual Conference of the Cognitive Science Society, ed. Hahn, M. & Stones, S. C. Erlbaum. [PT]Google Scholar
Lave, J. (1988) Cognition in practice: Mind, mathematics, and culture in everyday life. Cambridge University Press. [aJRA]10.1017/CBO9780511609268CrossRefGoogle Scholar
Lebiere, C. (1998) The dynamics of cognition: An ACT-R model of cognitive arithmetic. Doctoral dissertation. CMU Computer Science Department Technical Report CMU-CS-98–186. Pittsburgh, PA. [aJRA]Google Scholar
Lebiere, C. & Anderson, J. R. (1993) A connectionist implementation of the ACTR production system. In: Proceedings of the Fifteenth Annual Conference of the Cognitive Science Society, pp. 635–40. Erlbaum. [aJRA]Google Scholar
Lerch, F. J., Gonzalez, C. & Lebiere, C. (1999) Learning under high cognitive workload. In: Proceedings of the Twenty-first Conference of the Cognitive Science Society. Erlbaum. [aJRA]Google Scholar
Lewis, R. L. (1999) Attachment without competition: A race-based model of ambiguity resolution in a limited working memory. Presented at the CUNY Sentence Processing Conference, New York. [aJRA]Google Scholar
Liben, L. S. (1987) Approaches to development and learning: Conflict and congruence. In: Development and learning: Conflict or congruence? ed. Liben, L. S. Erlbaum. [SS]Google Scholar
Lieberman, M. D. (2000) Intuition: A social cognitive neuroscience approach. Psychological Bulletin 126(1):109–37. [IP]10.1037/0033-2909.126.1.109CrossRefGoogle ScholarPubMed
Lieberman, M. D., Gaunt, R., Gilbert, D. T. & Trope, Y. (2002) Reflexion and reflection: A social cognitive neuroscience approach to attributional inference. Advances in Experimental Social Psychology 34:200–50. [IP]Google Scholar
Lodge, D. (1984) Small world. Penguin. [NAT]Google Scholar
Logan, G. D. (1988) Toward an instance theory of automatization. Psychological Review 95:492–527. [aJRA]10.1037/0033-295X.95.4.492CrossRefGoogle Scholar
Lovett, M. C. (1998) Choice. In: The atomic components of thought, ed. Anderson, J. R. & Lebiere, C. Erlbaum. [aJRA]Google Scholar
Lovett, M. C., Daily, L. Z. & Reder, L. M. (2000) A source activation theory of working memory: Cross-task prediction of performance in ACT-R. Cognitive Systems Research 1:99–118. [aJRA]10.1016/S1389-0417(99)00012-1CrossRefGoogle Scholar
Lovett, M. C., Reder, L. & Lebiere, C. (1997) Modeling individual differences in a digit working memory task. In: Proceedings of the 19th Annual Conference of the Cognitive Science Society, ed. Shafto, M. G.. & Langley, P. Erlbaum. [NAT]Google Scholar
MacDonald, M. C., Pearlmutter, N. J. & Seidenberg, M. S. (1994) The lexical nature of syntactic ambiguity resolution. Psychological Review 101:676–703. [aJRA]10.1037/0033-295X.101.4.676CrossRefGoogle ScholarPubMed
Magerman, D. (1995) Statistical decision-tree models for parsing. In: Proceedings of the 33rd Annual Meeting of the Association for Computational Linguistics, pp. 276–83. ACL. [aJRA]10.3115/981658.981695CrossRefGoogle Scholar
Marcus, G. F. (2001) The algebraic mind: Integrating connectionism and cognitive science. MIT Press. [aJRA, FCG, JLM]10.7551/mitpress/1187.001.0001CrossRefGoogle Scholar
Marcus, G. F., Brinkmann, U., Clahsen, H., Wiese, R. & Pinker, S. (1995) German inflection: The exception that proves the rule. Cognitive Psychology 29:189–256. [JLM]10.1006/cogp.1995.1015CrossRefGoogle ScholarPubMed
Marcus, G. F., Vijayan, S., Rao, S. B. & Vishton, P. M. (1999) Rule learning in seven-month-old infants. Science 283:77–80. [FCG]10.1126/science.283.5398.77CrossRefGoogle ScholarPubMed
Marín, J., Calvo, F. & Valenzuela, J. (2003) The creolization of pidgin: A connectionist exploration. In: Proceedings of the European Cognitive Science Conference, ed. Schmalhofer, F., Young, R. M. & Katz, G. Erlbaum. [FCG]Google Scholar
Marr, D. (1982) Vision. Freeman. [JA, PT, HW]Google Scholar
Massaro, D. W. (1989) Testing between the TRACE model and the fuzzy logical model of speech perception. Cognitive Psychology 21:398–421. [JLM]10.1016/0010-0285(89)90014-5CrossRefGoogle ScholarPubMed
Massaro, D. W. (1998) Perceiving talking faces: From speech perception to a behavioral principle. MIT Press. [PFMJV]Google Scholar
Massaro, D. W. & Cohen, M. M. (1991) Integration versus interactive activation: The joint influence of stimulus and context in perception. Cognitive Psychology 23:558–614. [JLM]10.1016/0010-0285(91)90006-ACrossRefGoogle ScholarPubMed
Matessa, M. (2001) Simulating adaptive communication. Doctoral dissertation, Carnegie Mellon University, Pittsburgh, PA. [aJRA]Google Scholar
Matessa, M. & Anderson, J. R. (2000) Modeling focused learning in role assignment. Language and Cognitive Processes 15:263–92. [aJRA]10.1080/016909600386057CrossRefGoogle Scholar
Mayr, E. (1988) Toward a new philosophy of biology: Observations of an evolutionist. Harvard University Press. [PAMG]Google Scholar
McClelland, J. L. (1979) On time relations of mental processes: An examination of systems of processes in cascade. Psychological Review 86:287–330. [aJRA]10.1037/0033-295X.86.4.287CrossRefGoogle Scholar
McClelland, J. L. (1991) Stochastic interactive processes and the effect of context on perception. Cognitive Psychology 23:1–44. [JLM]10.1016/0010-0285(91)90002-6CrossRefGoogle ScholarPubMed
McClelland, J. L. (1994) The interaction of nature and nurture in development: A parallel distributed processing perspective. In: International perspectives on psychological science, vol. 1: Leading themes, ed. Bertelson, P., Eelen, P. & D’Ydewalle, G. Erlbaum. [FCG]Google Scholar
McClelland, J. L. & Chappell, M. (1998) Familiarity breeds differentiation: A Bayesian approach to the effects of experience in recognition memory. Psychological Review 105:724–60. [aJRA]10.1037/0033-295X.105.4.734-760CrossRefGoogle Scholar
McClelland, J. L. & Elman, J. L. (1986) The TRACE model of speech perception. Cognitive Psychology 18:1–86. [JLM]10.1016/0010-0285(86)90015-0CrossRefGoogle ScholarPubMed
McClelland, J. L., McNaughton, B. L. & O’Reilly, R. C. (1995) Why there are complementary learning systems in the hippocampus and neocortex: Insights from the successes and failures of connectionist models of learning and memory. Psychological Review 102:419–57. [aJRA]10.1037/0033-295X.102.3.419CrossRefGoogle ScholarPubMed
McClelland, J. L. & Patterson, K. (2002a) Rules or connections in past-tense inflections: What does the evidence rule out? Trends in Cognitive Sciences 6:465–72. [JLM]10.1016/S1364-6613(02)01993-9CrossRefGoogle Scholar
McClelland, J. L. & Patterson, K. (2002b) ‘Words or Rules’ cannot exploit the regularity in exceptions. Trends in Cognitive Sciences 6:464–65. [JLM]CrossRefGoogle Scholar
McClelland, J. L. & Plaut, D. C. (1999) Does generalization in infant learning implicate abstract algebra-like rules? Trends in Cognitive Sciences 3:166–68. [aJRA]10.1016/S1364-6613(99)01320-0CrossRefGoogle ScholarPubMed
McClelland, J. L. & Rumelhart, D. E. (1981) An interactive activation model of context effects in letter perception: Part 1. An account of basic findings. Psychological Review 88(5):375–407. [aJRA,JLM]10.1037/0033-295X.88.5.375CrossRefGoogle Scholar
McClelland, J. L. & Rumelhart, D. E. (1986) Parallel distributed processing. Explorations in the microstructure of cognition, vol. 2. MIT Press/Bradford. [aJRA]Google Scholar
McCloskey, M. & Cohen, N. J. (1989) Catastrophic interference in connectionist networks: The sequential learning problem. In: The psychology of learning and motivation: Advances in research and theory, vol. 24, ed. Bower, G. H. Academic Press. [aJRA]Google Scholar
Menzel, R. & Muller, U. (1996) Learning and memory in honeybees: From behavior to neural substrate. Annual Review Neuroscience 19:379–404. [PFMJV]10.1146/annurev.ne.19.030196.002115CrossRefGoogle Scholar
Meyer, D. E. & Kieras, D. E. (1997) A computational theory of executive cognitive processes and multiple-task performance. Part 1. Basic mechanisms. Psychological Review 104:2–65. [arJRA]Google ScholarPubMed
Minsky, M. L. & Papert, S. A. (1969) Perceptrons. MIT Press. [aJRA]Google Scholar
Misker, J. M. V. & Anderson, J. R. (2003) Combining optimality theory and a cognitive architecture. In: Proceedings of the Fifth International Conference on Cognitive Modeling, Bamberg, Germany, April 2003, pp. 171–76, ed. Detje, F., Dorner, D. & Straub, H. Univeritäts-Verlag Bamberg. [rJRA]Google Scholar
Movellan, J. R. & McClelland, J. L. (2001) The Morton-Massaro law of information integration: Implications for models of perception. Psychological Review 108(1):113–48. [JLM]CrossRefGoogle ScholarPubMed
Nagel, T. (1974) What is it like to be a bat? Philosophical Review 83:435–51. [MO]CrossRefGoogle Scholar
Newcombe, N. (1998) Defining the “radical middle.” Human Development 41:210–14. [CFO]10.1159/000022582CrossRefGoogle Scholar
Newell, A. (1973) You can't play 20 questions with nature and win: Projective comments on the papers of this symposium. In: Visual information processing, ed. Chase, W. G. Academic Press. [EMA, arJRA, YY]Google Scholar
Newell, A. (1980) Physical symbol systems. Cognitive Science 4:135–83. [arJRA, WJC, PAMG, SS]Google Scholar
Newell, A. (1990) Unified theories of cognition. Harvard University Press. [arJRA, WJC, PAMG, WDG, AGBtM, SS, HW, RMY]Google Scholar
Newell, A. (1992) Précis of Unified theories of cognition. Behavioral and Brain Sciences 15:425–92. [aJRA, MLC]CrossRefGoogle Scholar
Newell, A. & Card, S. K. (1985) The prospects for psychological science in humancomputer interaction. Human-Computer Interaction 1(3):209–42. [WDG]CrossRefGoogle Scholar
Newell, A. & Simon, H. A. (1963/1995) GPS, a program that simulates human thought. In: Computers and thought, ed. Feigenbaum, E., Feldman, J. & Armer, P. AAAI Press. [MLC]Google Scholar
Newell, A. & Simon, H. A. (1972) Human problem solving. Prentice Hall. [aJRA]Google Scholar
Norman, D. A. & Shallice, T. (1986) Attention to action: Willed and automatic control of behaviour. In: The design of everyday things, ed. Davidson, R. J., Schwartz, G. E. & Shapiro, D. Doubleday. [MO]Google Scholar
Oaksford, M. & Chater, N., eds. (1998) Rational models of cognition. Oxford University Press. [aJRA]Google Scholar
O’Hear, A. (1997) Beyond evolution: Human nature and the limits of evolutionary explanation. Clarendon Press. [PAMG]Google Scholar
Ohlsson, S. & Jewett, J. J. (1997) Simulation models and the power law of learning. Proceedings of the 19th Annual Conference of the Cognitive Science Society, ed. Cognitive Science Society. Erlbaum. [PT]Google Scholar
O’Reilly, R. & Munakata, Y. (2000) Computational explorations in cognitive neuroscience: Understanding the mind by simulating the brain. MIT Press. [FCG, HW]10.7551/mitpress/2014.001.0001CrossRefGoogle Scholar
Overgaard, M. (2003) On the theoretical and methodological foundations for a science of consciousness. Bulletin from Forum for Antropologisk Psykologi 13:6–31. [MO]Google Scholar
Palmer-Brown, D., Tepper, J. A. & Powell, H. M. (2002) Connectionist natural language parsing. Trends in Cognitive Sciences 6:437–42. [FCG]10.1016/S1364-6613(02)01980-0CrossRefGoogle ScholarPubMed
Partee, B. (1984) Nominal and temporal anaphora. Linguistics and Philosophy 7:243–86. [AGBtM]CrossRefGoogle Scholar
Partee, B. (1997) Montague grammar. In: Handbook of logic and language, ed. van Benthem, J. & ter Meulen, A. G. B. Elsevier Science/MIT Press. [AGBtM]Google Scholar
Pashler, H. (1998) The psychology of attention. MIT Press. [aJRA]Google Scholar
Pavlov, I. P. (1928) Lectures on conditioned reflexes: Twenty-five years of objective study of the higher nervous ability (behavior) of animals. International Publishers. [PFMJV]Google Scholar
Penrose, R. (1989) The emperor's new mind: Concerning computers, minds, and the laws of physics. Oxford University Press. [HW]10.1093/oso/9780198519737.001.0001CrossRefGoogle Scholar
Penrose, R. (1996) Shadows of the mind: A search for the missing science of consciousness. Oxford University Press. [HW]10.1093/oso/9780195106466.001.0001CrossRefGoogle Scholar
Penrose, R. (1997) The large, the small and the human mind. Cambridge University Press. [HW]Google Scholar
Piaget, J. (1967/1971) Biology and Knowledge. University of Chicago Press. [PAMG]Google Scholar
Pinker, S. (1991) Rules of language. Science 253:530–35. [JLM]10.1126/science.1857983CrossRefGoogle ScholarPubMed
Pinker, S. (1994) The language instinct. Morrow. [aJRA]CrossRefGoogle Scholar
Pinker, S. (1997) How the mind works. Norton. [IP]Google Scholar
Pinker, S. & Bloom, P. (1990) Natural language and natural selection. Behavioral and Brain Sciences 13(4):707–84. [aJRA]10.1017/S0140525X00081061CrossRefGoogle Scholar
Pinker, S. & Ullman, M. T. (2002a) The past and future of the past tense. Trends in Cognitive Sciences 6:456–63. [JLM]10.1016/S1364-6613(02)01990-3CrossRefGoogle Scholar
Pinker, S. & Ullman, M. T. (2002b) Combination and structure, not gradedness, is the issue. Trends in Cognitive Sciences 6:472–74. [JLM]10.1016/S1364-6613(02)02013-2CrossRefGoogle Scholar
Plaut, D. C. & Booth, J. R. (2000) Individual and developmental differences in semantic priming: Empirical and computational support for a single-mechanism account of lexical processing. Psychological Review 107:786–823. [aJRA]CrossRefGoogle ScholarPubMed
Plaut, D. C., McClelland, J. L. & Seidenberg, M. S. (1995) Reading exception words and pseudowords: Are two routes really necessary? In: Connectionist models of memory and language, ed. Levy, J. P., Bairaktaris, D., Bullinaria, J. A. & Cairns, P. UCL Press. [JLM]Google Scholar
Plaut, D. C., McClelland, J. L., Seidenberg, M. S. & Patterson, K. (1996) Understanding normal and impaired word reading: Computational principles in quasi-regular domains. Psychological Review 103:56–115. [JLM]CrossRefGoogle ScholarPubMed
Plunkett, K., Karmiloff-Smith, A., Bates, E., Elman, J. L. & Johnson, M. H. (1997) Connectionism and developmental psychology. Journal of Child Psychology and Psychiatry 38:53–80. [CFO]CrossRefGoogle ScholarPubMed
Plunkett, K. & Marchman, V. A. (1991) U-shaped learning and frequency effects in a multi-layered perceptron: Implications for child language acquisition. Cognition 38:43–102. [JLM]CrossRefGoogle Scholar
Pollen, D. A. (1999) On the neural correlates of visual perception. Cerebral Cortex 9:4–19. [SG]10.1093/cercor/9.1.4CrossRefGoogle ScholarPubMed
Pomerleau, D. A. (1991) Efficient training of artificial neural networks for autonomous navigation. Neural Computation 3:88–97. [aJRA]10.1162/neco.1991.3.1.88CrossRefGoogle ScholarPubMed
Pomerleau, D. A., Gowdy, J. & Thorpe, C. E. (1991) Combining artificial neural networks and symbolic processing for autonomous robot guidance. Engineering Applications of Artificial Intelligence 4:279–85. [aJRA]CrossRefGoogle Scholar
Popper, K. R. (1963) Conjectures and refutations: The growth of scientific knowledge. Routledge. [NAT]Google Scholar
Prince, A. & Smolensky, P. (1993) Optimality theory: Constraint interaction in generative grammar. Technical Report CU-CS-696–93, Department of Computer Science, University of Colorado at Boulder, and Technical Report TR-2, Rutgers Center for Cognitive Science, Rutgers University, New Brunswick, NJ. April. [rJRA]Google Scholar
Prudkov, P. (1994) A model of self-organization of cognitive processes. Cognitive Systems 4(1):1–19. [PNP]Google Scholar
Pyysiäinen, I. (2003) True fiction: Philosophy and psychology of religious belief. Philosophical Psychology 16(1):109–25. [IP]10.1080/0951508032000067716CrossRefGoogle Scholar
Qin, Y., Sohn, M-H, Anderson, J. R., Stenger, V. A., Fissell, K., Goode, A. & Carter, C. S. (2003) Predicting the practice effects on the blood oxygenation level-dependent (BOLD) function of fMRI in a symbolic manipulation task. Proceedings of the National Academy of Sciences USA 100(8):4951–56. [rJRA]10.1073/pnas.0431053100CrossRefGoogle Scholar
Quartz, S. R. (1993) Neural networks, nativism, and the plausibility of constructivism. Cognition 48:223–42. [SS]CrossRefGoogle ScholarPubMed
Quinn, R. & Espenschied, K. (1993) Control of a hexapod robot using a biologically inspired neural network. In: Biological neural networks in invertebrate neuroethology and robotics, ed. Beer, R. et al. Academic Press. [DS]Google Scholar
Raizada, R. & Grossberg, S. (2003) Towards a theory of the laminar architecture of cerebral cortex: Computational clues from the visual system. Cerebral Cortex 13:100–13. [SG]CrossRefGoogle ScholarPubMed
Ramscar, M. (2002) The role of meaning in inflection: Why the past tense does not require a rule. Cognitive Psychology 45(1):45–94. [JLM]10.1016/S0010-0285(02)00001-4CrossRefGoogle Scholar
Ratcliff, R. (1990) Connectionist models of recognition memory: Constraints imposed by learning and forgetting functions. Psychological Review 97:285–308. [aJRA]10.1037/0033-295X.97.2.285CrossRefGoogle ScholarPubMed
Ratcliff, R., Van Zandt, T.& McKoon, G. (1999) Connectionist and diffusion models of reaction time. Psychological Review 106:261–300. [aJRA]CrossRefGoogle ScholarPubMed
Reder, L. M., Nhouyvansivong, A., Schunn, C. D., Ayers, M. S., Angstadt, P. & Hiraki, K. (2000) A mechanistic account of the mirror effect for word frequency: A computational model of remember/know judgments in a continuous recognition paradigm. Journal of Experimental Psychology: Learning, Memory, and Cognition 26:294–320. [aJRA]Google Scholar
Revonsuo, A. & Kampinnen, M., eds. (1994) Consciousness in philosophy and cognitive neuroscience. Erlbaum. [PAMG]Google Scholar
Roberts, S. & Pashler, H. (2000) How persuasive is a good fit? A comment on theory testing. Psychological Review 107:358–67. [aJRA]CrossRefGoogle Scholar
Rogers, R. D. & Monsell, S. (1995) Costs of a predictable switch between simple cognitive tasks. Journal of Experimental Psychology: General 124(2):207–31. [EMA, WDG]10.1037/0096-3445.124.2.207CrossRefGoogle Scholar
Rogers, T. T. & McClelland, J. L. (in press) Semantic cognition: A parallel distributed processing approach. MIT Press. [aJRA]10.7551/mitpress/6161.001.0001CrossRefGoogle Scholar
Rolls, E. T. (2000) Memory systems in the brain. Annual Reviews, Psychology 51(1):599–630. [IP]CrossRefGoogle ScholarPubMed
Rolls, E. T. & Treves, A. (1998) Neural networks and brain function. Oxford University Press. [FCG]Google Scholar
Roy, A., Govil, S. & Miranda, R. (1997) A neural network learning theory and a polynomial time RBF algorithm. IEEE Transactions on Neural Networks 8(6):1301–13. [AR]CrossRefGoogle Scholar
Rumelhart, D. E. & McClelland, J. L. (1982) An interactive activation model of context effects in letter perception: Part 2. The contextual enhancement effect and some tests and extensions of the model. Psychological Review 89:60–94. [aJRA]10.1037/0033-295X.89.1.60CrossRefGoogle ScholarPubMed
Rumelhart, D. E. & McClelland, J. L. (1986a) On learning the past tenses of English verbs. In: Parallel distributed processing: Explorations in the microstructure of cognition, vol. 2, ed. McClelland, J. L., Rumelhart, D. E. & the PDP Research Group. MIT Press. [JLM]10.7551/mitpress/5236.001.0001CrossRefGoogle Scholar
Rumelhart, D. E. & McClelland, J. L. (1986b) PDP models and general issues in cognitive science. In: Parallel distributed processing: Explorations in the microstructure of cognition: Foundations, vol. 1, ed. McClelland, J. L., Rumelhart, D. E. & The PDP Research Group. MIT Press. [aJRA]CrossRefGoogle Scholar
Rumelhart, D. E., McClelland, J. L. & the PDP Research Group (1986) Parallel distributed processing: Explorations in the microstructure of cognition: Vol. I: Foundations; Vol. II: Psychological and biological models. MIT Press. [JLM, AR, RS]Google Scholar
Salvucci, D. D. (2001) Predicting the effects of in-car interface use on driver performance: An integrated model approach. International Journal of Human-Computer Studies 55:85–107. [rJRA]10.1006/ijhc.2001.0472CrossRefGoogle Scholar
Salvucci, D. D. & Anderson, J. R. (2001) Integrating analogical mapping and general problem solving: The path-mapping theory. Cognitive Science 25:67–110. [aJRA]Google Scholar
Sanchez-Montanes, M. A., König, P. & Verschure, P. F. M. J. (2002) Learning sensory maps with real-world stimuli in real time using a biophysically realistic learning rule. IEEE Transactions on Neural Networks 13:619–32. [PFMJV]CrossRefGoogle ScholarPubMed
Sanner, S., Anderson, J. R., Lebiere, C. & Lovett, M. (2000) Achieving efficient and cognitively plausible learning in backgammon. In: Proceedings of the Seventeenth International Conference on Machine Learning. Morgan Kaufmann. [aJRA]Google Scholar
Schneider, W. & Oliver, W. L. (1991) An instructable connectionist/control architecture: Using rule-based instructions to accomplish connectionist learning in a human time scale. In: Architecture for intelligence: The 22nd Carnegie Mellon Symposium on Cognition, ed. Van Lehn, K. Erlbaum. [aJRA]Google Scholar
Schoelles, M. J. (2002) Simulating human users in dynamic environments. Unpublished doctoral dissertation, George Mason University, Fairfax, VA. [WDG]Google Scholar
Schoelles, M. J. & Gray, W. D. (2003) Top-down versus bottom-up control of cognition in a task switching paradigm, Fifth International Conference on Cognitive Modeling. Bamberg. [WDG]Google Scholar
Schoppek, W. (2001) The influence of causal interpretation on memory for system states. In: Proceedings of the 23rd Annual Conference of the Cognitive Science Society, ed. Moore, J. D. & Stenning, K. Erlbaum. [aJRA]Google Scholar
Seidenberg, M. S. & McClelland, J. L. (1989) A distributed, developmental model of word recognition and naming. Psychological Review 96:523–68. [JLM]10.1037/0033-295X.96.4.523CrossRefGoogle ScholarPubMed
Sejnowski, T. J. & Rosenberg, C. R. (1987) Parallel networks that learn to pronounce English text. Complex Systems 1:145–68. [aJRA]Google Scholar
Shastri, L., Grannes, D., Narayanan, S. & Feldman, J. (2002) A connectionist encoding of parameterized schemas and reactive plans. In: Hybrid information processing in adaptive autonomous vehicles, ed. Kraetzschmar, G. K. & Palm, G. Springer-Verlag. [RS]Google Scholar
Sherrington, C. (1906) The integrative action of the nervous system. Charles Scribner’s. [PAMG]Google Scholar
Shirai, Y. & Anderson, R. W. (1995) The acquisition of tense-aspect morphology: A prototype account. Language 71:743–62. [JLM]10.2307/415743CrossRefGoogle Scholar
Siegelman, H. T. & Sontag, E. D. (1992) On the computational power of neural nets. In: Proceedings of the 5th ACM Workshop on Computational Learning Theory. ACM. [aJRA]Google Scholar
Siegelmann, H. (1999) Neural networks and analog computation: Beyond the Turing Limit. Birkhauser. [YY]CrossRefGoogle Scholar
Siegler, R. S. (1988) Strategy choice procedures and the development of multiplication skill. Journal of Experimental Psychology: General 117:258–75. [aJRA]10.1037/0096-3445.117.3.258CrossRefGoogle ScholarPubMed
Siegler, R. S. & Lemaire, P. (1997) Older and younger adults’ strategy choices in multiplication: Testing predictions of ASCM using the choice/no-choice method. Journal of Experimental Psychology: General 126(1):71–92. [WDG]10.1037/0096-3445.126.1.71CrossRefGoogle ScholarPubMed
Siegler, R. S. & Stern, E. (1998) Conscious and unconscious strategy discoveries: A microgenetic analysis. Journal of Experimental Psychology: General 127(4):377–97. [WDG]CrossRefGoogle ScholarPubMed
Simon, L., Greenberg, J., Harmon-Jones, E., Solomon, S., Pyszczynski, T., Arndt, J. & Abend, T. (1997) Terror management and cognitive-experiential self-theory: Evidence that terror management occurs in the experiential system. Personality and Social Psychology 72(5):1132–46. [IP]10.1037/0022-3514.72.5.1132CrossRefGoogle ScholarPubMed
Simon, T. J. (1998) Computational evidence for the foundations of numerical competence. Developmental Science 1:71–78. [aJRA]10.1111/1467-7687.00015CrossRefGoogle Scholar
Simon, T. J. (1998) (submitted) De-mystifying magical object appearance with a theory of the foundations of numerical competence. Developmental Science. [aJRA]10.1111/1467-7687.00015CrossRefGoogle Scholar
Sirois, S. & Mareschal, D. (2002) Computational approaches to infant habituation. Trends in Cognitive Sciences 6:293–98. [SS]CrossRefGoogle Scholar
Sirois, S. & Shultz, T. R. (1999) Learning, development, and nativism: Connectionist implications. In: Proceedings of the Twenty-first Annual Conference of the Cognitive Science Society, ed. Hahn, M. & Stoness, S. C. Erlbaum. [SS]Google Scholar
Sirois, S. & Shultz, T. R. (2003) A connectionist perspective on Piagetian development. In: Connectionist models of development, ed. Quinlan, P. Psychology Press. [SS]Google Scholar
Sloman, S. A. (1996) The empirical case for two systems of reasoning. Psychological Bulletin 119(1):3–22. [IP]CrossRefGoogle Scholar
Sloman, S. A. (1999) Rational versus arational models of thought. In: The nature of cognition, ed. Sternberg, R. J. MIT Press. [IP]Google Scholar
Smith, E. R. & DeCoster, J. (2000) Dual-process models in social and cognitive psychology: Conceptual integration and links to underlying memory systems. Personality and Social Psychology Review 4(2):108–31. [IP]CrossRefGoogle Scholar
Smolensky, P. (1988) On the proper treatment of connectionism. Behavioral and Brain Sciences 11:1–74. [aJRA]10.1017/S0140525X00052432CrossRefGoogle Scholar
Sohn, M.-H. & Anderson, J. R. (2001) Task preparation and task repetition: Twocomponent model of task switching. Journal of Experimental Psychology: General 130:764–78. [EMA]10.1037/0096-3445.130.4.764CrossRefGoogle ScholarPubMed
Sohn, M.-H., Goode, A., Stenger, V. A. Carter, C. S. & Anderson, J. R. (2003). Competition and representation during memory retrieval: Roles of the prefrontal cortex and the posterior parietal cortex. Proceedings of the National Academy of Sciences USA 100:7412–17. [rJRA]10.1073/pnas.0832374100CrossRefGoogle ScholarPubMed
Sohn, M.-H., Ursu, S., Anderson, J. R., Stenger, V. A. & Carter, C. S. (2000) The role of prefrontal cortex and posterior parietal cortex in task-switching. Proceedings of the National Academy of Science 13:448–53. [aJRA]Google Scholar
Sperber, D. (1997) Intuitive and reflective beliefs. Mind and Language 12(1):67–83. [IP]CrossRefGoogle Scholar
Squire, L. R. (1992) Memory and the hippocampus: A synthesis from findings with rats, monkeys, and humans. Psychological Review 99:195–232. [aJRA]10.1037/0033-295X.99.2.195CrossRefGoogle ScholarPubMed
Suchman, L. A. (1987) Plans and situated actions: The problem of human-machine communication. Cambridge University Press. [aJRA]Google Scholar
Sun, R. (1994) Integrating rules and connectionism for robust commonsense reasoning. Wiley. [aJRA, IP, RS]Google Scholar
Sun, R. (2002) Duality of the mind: A bottom-up approach toward cognition. Erlbaum. [aJRA, IP, RS]Google Scholar
Sun, R. & Bookman, L., eds. (1994) Computational architectures integrating neural and symbolic processes. A perspective on the state of the art. Kluwer. [IP, RS]Google Scholar
Sun, R., Merrill, E. & Peterson, T. (2001) From implicit skills to explicit knowledge: A bottom-up model of skill learning. Cognitive Science 25(2):203–44. [RS]Google Scholar
Taatgen, N. A. (2001) Extending the past-tense debate: A model of the German plural. Proceedings of the Twenty-third Annual Conference of the Cognitive Science Society, pp. 1018–23. Erlbaum. [aJRA]Google Scholar
Taatgen, N. A. (2002) A model of individual differences in skill acquisition in the Kanfer-Ackerman air traffic control task. Cognitive Systems Research 3:103–12. [aJRA, NAT]CrossRefGoogle Scholar
Taatgen, N. & Anderson, J. R. (2002) Why do children learn to say “broke”? A model of learning the past tense without feedback. Cognition 86:(2)123–55. [arJRA, JLM, AGBtM, PNP]10.1016/S0010-0277(02)00176-2CrossRefGoogle Scholar
Taatgen, N. & Dijkstra, M. (2003) Constraints on generalization: Why are pasttense irregularization errors so rare? Proceedings of the 25th Annual Conference of the Cognitive Science Society. Erlbaum. [rJRA]Google Scholar
Taatgen, N. A. & Lee, F. J. (2003). Production composition: A simple mechanism to model complex skill acquisition. Human Factors 45(1):61–76. [WDG]CrossRefGoogle Scholar
ter Meulen, A. (1995) Representing time in natural language: The dynamic interpretation of tense and aspect. Bradford Books. [AGBtM]10.7551/mitpress/5897.001.0001CrossRefGoogle Scholar
ter Meulen, A. (2000) Chronoscopes: The dynamic representation of facts and events. In: Speaking about events, ed. Higginbotham, J., Pianesi, F. & Varzi, A. Oxford University Press. [AGBtM]Google Scholar
Tesauro, G. (2002) Programming backgammon using self-teaching neural nets. Artificial Intelligence 134:181–99. [aJRA]10.1016/S0004-3702(01)00110-2CrossRefGoogle Scholar
Thagard, P. (1992) Conceptual revolutions. Princeton University Press. [CFO]CrossRefGoogle Scholar
Thelen, E. & Smith, L. B. (1994) A dynamic systems approach to the development of cognition and action. MIT Press. [DS]10.7551/mitpress/2524.001.0001CrossRefGoogle Scholar
Thomas, M. S. C. & Karmiloff-Smith, A. (2002) Are developmental disorders like cases of adult brain damage? Implications from connectionist modelling. Behavioral and Brain Sciences 25(6):727–88. [CFO]CrossRefGoogle ScholarPubMed
Thomas, M. S. C. & Karmiloff-Smith, A. (2003) Modelling language acquisition in atypical phenotypes. Psychological Review 110(4):647–82. [CFO]10.1037/0033-295X.110.4.647CrossRefGoogle ScholarPubMed
Tolman, E. C. (1948) Cognitive maps in rats and men. Psychological Review 55:189–208. [MO]10.1037/h0061626CrossRefGoogle ScholarPubMed
Treisman, A. M. & Gelade, G. (1980) A feature integration theory of attention. Cognitive Psychology 12:97–136. [MO]10.1016/0010-0285(80)90005-5CrossRefGoogle ScholarPubMed
Turing, A. (1950) Computing machinery and intelligence. Mind 49:433–60. [NAT]10.1093/mind/LIX.236.433CrossRefGoogle Scholar
Ullman, M. T., Corkin, S., Coppola, M., Hicock, G., Growdon, J. H., Koroshetz, W. J. & Pinker, S. (1997) A neural dissociation within language: Evidence that themental dictionary is part of declarative memory and that grammatical rules are processed by the procedural system. Journal of Cognitive Neuroscience 9:266–76. [JLM]10.1162/jocn.1997.9.2.266CrossRefGoogle Scholar
Usher, M. & McClelland, J. L. (2001) On the time course of perceptual choice: The leaky competing accumulator model. Psychological Review 108:550–92. [JLM]10.1037/0033-295X.108.3.550CrossRefGoogle ScholarPubMed
van Eijck, J. & Kamp, H. (1997) Representing discourse in context. In: Handbook of logic and language, ed. van Benthem, J. & ter Meulen, A. G. B. Elsevier Science/MIT Press. [AGBtM]Google Scholar
van Rijn, H., Someren, M. & van der Maas, H. (2000) Modeling developmental transitions in ACT-R. Simulating balance scale behavior by symbolic and subsymbolic learning. In: Proceedings of the 3rd International Conference on Cognitive Modeling, pp. 226–33. Universal Press. [aJRA]Google Scholar
Vargha-Khadem, F., Watkins, K., Alcock, K., Fletcher, P. & Passingham, R. (1995) Praxic and nonverbal cognitive deficits in a large family with a genetically transmitted speech and language disorder. Proceedings of the National Academy of Science 92:930–33. [JLM]10.1073/pnas.92.3.930CrossRefGoogle Scholar
Velmans, M. (1991) Is human information processing conscious? Behavioral and Brain Sciences 14(4):651–726. [MO]10.1017/S0140525X00071776CrossRefGoogle Scholar
Velmans, M., ed. (1996) The science of consciousness: Psychological, neuropsychological and clinical reviews. Routledge. [PAMG]Google Scholar
Vere, S. A. (1992) A cognitive process shell. Behavioral and Brain Sciences 15:460–61. [aJRA]10.1017/S0140525X00069703CrossRefGoogle ScholarPubMed
Verkuyl, H. (1996) A theory of aspectuality: The interaction between temporal and atemporal structure. Cambridge University Press. [AGBtM]Google Scholar
Verschure, P. F. M. J. (1990) Smolensky's theory of mind. Behavioral and Brain Sciences 13:407. [PFMJV]CrossRefGoogle Scholar
Verschure, P. F. M. J. (1992) Taking connectionism seriously: The vague promise of subsymbolism and an alternative. Proceedings of the 14th Annual Conference of the Cognitive Science Society, pp. 653–58. Erlbaum. [PFMJV]Google Scholar
Verschure, P. F. M. J. (1998) Synthetic epistemology: The acquisition, retention, and expression of knowledge in natural and synthetic systems. In: Proceedings 1998 IEEE World Conference on Computational Intelligence, pp. 147–153. IEEE. [PFMJV]Google Scholar
Verschure, P. F. M. J. & Althaus, P. (2003) A real-world rational agent: Unifying old and new AI. Cognitive Science 27:561–90. [PFMJV]Google Scholar
Verschure, P. F. M. J., Kröse, B. J. A. & Pfeifer, R. (1992) Distributed adaptive control: The self-organization of structured behavior. Robotics and Autonomous Systems 9:181–96.10.1016/0921-8890(92)90054-3CrossRefGoogle Scholar
Verschure, P. F. M. J. & Voegtlin, T. (1998) A bottom-up approach towards the acquisition, retention, and expression of sequential representations: Distributed adaptive control, III. Neural Networks 11:1531–49. [PFMJV]10.1016/S0893-6080(98)00029-XCrossRefGoogle Scholar
Verschure, P. F. M. J., Voegtlin, T. & Douglas, R. J. (2003) Environmentally mediated synergy between perception and behaviour in mobile robots. Nature 425:620–624. [PFMJV]10.1038/nature02024CrossRefGoogle ScholarPubMed
Verschure, P. F. M. J., Wray, J., Sporns, O., Tononi, G. & Edelman, G. M. (1996) Multilevel analysis of classical conditioning in a behaving real world artifact. Robotics and Autonomous Systems 16:247–65. [PFMJV]10.1016/0921-8890(95)00050-XCrossRefGoogle Scholar
Voegtlin, T. & Verschure, P. F. M. J. (1999) What can robots tell us about brains? A synthetic approach towards the study of learning and problem solving. Reviews in the Neurosciences 10:291–310. [PFMJV]10.1515/REVNEURO.1999.10.3-4.291CrossRefGoogle Scholar
Waddington, C. H. (1975) The evolution of an evolutionist. Edinburgh University Press. [CFO]Google Scholar
Wallach, D. & Lebiere, C. (2000) Learning of event sequences: An architectural approach. In: Proceedings of the 3rd International Conference on Cognitive Modeling, ed. Taatgen, N. Universal Press. [aJRA]Google Scholar
Wallach, D. & Lebiere, C. (in press) Conscious and unconscious knowledge: Mapping to the symbolic and subsymbolic levels of a hybrid architecture. In: Attention and implicit learning, ed. Jimenez, L. John Benjamins. [aJRA]Google Scholar
Weizenbaum, J. (1966) ELIZA – A computer program for the study of natural language communication between man and machine. Communications of the Association for Computing Machinery 9:36–45. [NAT]10.1145/365153.365168CrossRefGoogle Scholar
Wermter, S. & Sun, R., eds. (2000) Hybrid neural systems (Lecture Notes in Artificial Intelligence, LNCS 1778). Springer-Verlag. [RS]10.1007/10719871CrossRefGoogle Scholar
Whitehouse, H. (2002) Modes of religiosity: Towards a cognitive explanation of the sociopolitical dynamics of religion. Method and Theory in the Study of Religion 14(3–4):293–315. [IP]10.1163/157006802320909738CrossRefGoogle Scholar
Wise, S. P., Murray, E. A. & Gerfen, C. R. (1996) The frontal cortex–basal ganglia system in primates. Critical Reviews in Neurobiology 10:317–56. [aJRA]10.1615/CritRevNeurobiol.v10.i3-4.30CrossRefGoogle ScholarPubMed
Woolf, N. J. & Hameroff, S. R. (2001) A quantum approach to visual consciousness. Trends in Cognitive Sciences 5(11):472–78. [HW]CrossRefGoogle ScholarPubMed
Yang, Y. & Bringsjord, S. (forthcoming) Mental metalogic: A new, unifying theory of human and machine reasoning. Erlbaum. [YY]Google Scholar