Jump to ContentJump to Main Navigation
Anatomy of the MindExploring Psychological Mechanisms and Processes with the Clarion Cognitive Architecture$

Ron Sun

Print publication date: 2016

Print ISBN-13: 9780199794553

Published to Oxford Scholarship Online: June 2016

DOI: 10.1093/acprof:oso/9780199794553.001.0001

Show Summary Details
Page of

PRINTED FROM OXFORD SCHOLARSHIP ONLINE (www.oxfordscholarship.com). (c) Copyright Oxford University Press, 2017. All Rights Reserved. Under the terms of the licence agreement, an individual user may print out a PDF of a single chapter of a monograph in OSO for personal use (for details see http://www.oxfordscholarship.com/page/privacy-policy). Subscriber: null; date: 21 January 2017

(p.405) References

(p.405) References

Source:
Anatomy of the Mind
Publisher:
Oxford University Press

Bibliography references:

Ahlum-Heath, M. & DiVesta, F. (1986). The effect of conscious controlled verbalization of a cognitive strategy on transfer in problem solving. Memory and Cognition, 14, 281–285.

Alexander, J., Giesen, B., Munch, R., & Smelser, N. (Eds.). (1987). The micro-macro link. Berkeley, CA: University of California Press.

Anderson, J. R. (1983). The architecture of cognition. Cambridge, MA: Harvard University Press.

Anderson, J. R. (1993). Rules of the mind. Hillsdale, NJ: Lawrence Erlbaum Associates.

Anderson, J. R. (2007). How can the human mind occur in the physical universe? New York: Oxford University Press.

Anderson, J. R. & Lebiere, C. (1998). The atomic components of thought. Mahwah, NJ: Lawrence Erlbaum Associates.

Anderson, J. R. & Lebiere, C. L. (2003). The Newell test for a theory of cognition. Behavioral and Brain Science, 26, 587–637.

Atran, S. & Norenzayan, A. (2004). Religion’s evolutionary landscape: Counterintuition, commitment, compassion, communion. Behavioral and Brain Sciences, 27(6), 713–730.

Axelrod, R. (1984). The evolution of cooperation. New York: Basic Books.

Baddeley, A. (1986). Working memory. New York: Oxford University Press.

Bach, J. (2009). Principles of synthetic intelligence PSI: An architecture of motivated cognition. New York: Oxford University Press.

Bandura, A. (1997). Self-efficacy: The exercise of control. New York: Freeman.

Barkow, J., Cosmides, L., & Tooby, J. (1992). The adapted mind: Evolutionary psychology and the generation of culture. New York: Oxford University Press. (p.406)

Baumeister, R. F. (1984). Choking under pressure: Self-consciousness and paradoxical effects of incentives on skillful performance. Journal of Personality and Social Psychology, 46, 610–620.

Bechtel, W. (2003). Modules, brain parts, and evolutionary psychology. In S. J. Scher and F. Rauscher (Eds.), Evolutionary psychology: Alternative approaches. Dordrecht: Kluwer.

Beilock, S. & Carr, T. (2001). On the fragility of skilled performance: What governs choking under pressure? Journal of Experimental Psychology: General, 130(4), 701–725.

Beilock, S., Kulp, C., Holt, L., & Carr, T. (2004), More on the fragility of performance: Choking under pressure in mathematical problem solving. Journal of Experimental Psychology: General, 133(4), 584–600.

Bennis, W. M., Medin, D. L., & Bartels, D. M. (2010). The costs and benefits of calculation and moral rules. Perspectives on Psychological Science, 5, 187–202.

Berry, D. (1983). Metacognitive experience and transfer of logical reasoning. Quarterly Journal of Experimental Psychology, 35A, 39–49.

Berry, D. (1991). The role of action in implicit learning. Quarterly Journal of Experimental Psychology, 43A, 881–906.

Berry, D. & Broadbent, D. (1984). On the relationship between task performance and associated verbalizable knowledge. Quarterly Journal of Experimental Psychology, 36A, 209–231.

Berry, D. & Broadbent, D. (1988). Interactive tasks and the implicit-explicit distinction. British Journal of Psychology, 79, 251–272.

Bertsekas, D. & Tsitsiklis, J. (1996). Neuro-dynamic programming. Belmont, MA: Athena Scientific.

Bickhard, M. (1993). Representational content in humans and machines. Journal of Experimental and Theoretical Artificial Intelligence, 285–333.

Bourdieu, P. & Wacquant, I. (1992). An invitation to reflexive sociology. Chicago: University of Chicago Press.

Bower, A. & King, W. (1967). The effect of number of irrelevant stimulus dimensions, verbalization, and sex on learning biconditional classification rules. Psychonomic Science, 8(10), 453–454.

Bower, G. H. (1981). Mood and memory. American Psychologist, 36, 129–148.

Bowers, J. S. (2009). On the biological plausibility of grandmother cells: Implications for neural network theories in psychology and neuroscience. Psychological Review, 116, 220–251.

Bowers, K., Regehr, G., Balthazard, C., and Parker, K. (1990). Intuition in the context of discovery. Cognitive Psychology, 22, 72–110.

Boyer, P. & Ramble, C. (2001). Cognitive templates for religious concepts: Cross-cultural evidence for recall of counter-intuitive representations. Cognitive Science, 25, 535–564. (p.407)

Braine, M. & O’Brien, D. (Eds.). (1998). Mental logic. Mahwah, NJ: Lawrence Erlbaum Associates.

Braitenberg, V. (1984). Vehicles: Experiments in synthetic psychology. Cambridge, MA: MIT Press.

Brooks, J. D., Wilson, N., & Sun, R. (2012). The effects of performance motivation: A computational exploration of a dynamic decision making task. Proceedings of the First International Conference on Brain-Mind (pp. 7–14). East Lansing, MI: BMI Press.

Brooks, R. (1991). Intelligence without representation. Artificial Intelligence, 47, 139–160.

Bruner, J., Goodnow, J., & Austin, J. (1956). A study of thinking. New York: Wiley.

Buckner, R. L., Petersen, S. E., Ojemann, J. G., Miezin, F. M., Squire, L. R., & Raichle, M. E. (1995). Functional anatomical studies of explicit and implicit memory retrieval tasks. Journal of Neuroscience, 15(1), 12–29.

Busemeyer, J. R. & Johnson, J. G. (2008). Micro-process models of decision making. In R. Sun (Ed.), Cambridge handbook of computational psychology (pp. 302–321). New York: Cambridge University Press.

Cacioppo, J. T., Gardner, W. L., & Berntson, G. G. (1999). The affect system has parallel and integrative processing components: Form follows function. Journal of Personality and Social Psychology, 76, 839–855.

Caprara, G. V. and D. Cervone, (2000). Personality: Determinants, Dynamics, and Potentials. New York: Cambridge University Press.

Carley, K. M., M. J. Prietula, and Z. Lin, (1998). Design versus cognition: The interaction of agent cognition and organizational design on organizational performance. Journal of Artificial Societies and Social Simulation, 1(3).

Carver, C. & Scheier, M. (1998). On the self-regulation of behavior. Cambridge, UK: Cambridge University Press.

Castelfranchi, C. (2001). The theory of social functions: challenges for computational social science and multi-agent learning. Cognitive Systems Research, 2(1), 5–38.

Cecconi, F. and D. Parisi, (1998). Individual versus social survival strategies. Journal of Artificial Societies and Social Simulation, 1(2). http://www.soc.surrey.ac.uk/JASSS/1/2/1.html

Cervone, D. (2004). The architecture of personality. Psychological Review, 111(1), 183–204.

Chaiken, S. & Trope, Y. (Eds.). (1999). Dual process theories in social psychology. New York: Guilford Press.

Chartier, S. and Proulx, R. (2005). NDRAM: A nonlinear dynamic recurrent associative memory for learning bipolar and nonbipolar correlated patterns. IEEE Transactions on Neural Networks, 16, 1393–1400. (p.408)

Chen, S., Shechter, D., & Chaiken, S. (1996). Getting at the truth or getting along: Accuracy- versus impression-motivated heuristic and systematic processing. Journal of Personality and Social Psychology, 71(2), 262–275.

Chi, M., M. Bassok, M. Lewis, P. Reimann, and P. Glaser, (1989). Self-explanation: How students study and use examples in learning to solve problems. Cognitive Science, 13, 145–182.

Chirkov, V. I., Ryan, R. M., & Willness, C. (2005). Cultural context and psychological needs in Canada and Brazil: Testing a self-determination approach to the internalization of cultural practices, identity, and well-being. Journal of Cross-Cultural Psychology, 36, 423–443.

Chomsky, N. (1980). Rules and representation. New York: Columbia University Press.

Chong, H., Tan, A., & Ng, G. (2007). Integrated cognitive architectures: A survey. Artificial Intelligence Review, 28(2), 103–130.

Clancey, W. J. (1997). Situated cognition: On human knowledge and computer representation. New York: Cambridge University Press.

Clark, L. A., & Watson, D. (1999). Temperament: A new paradigm for trait psychology. In L. A. Pervin & O. P. John (Eds.), Handbook of personality: Theory and research (2d ed.) (pp. 399–423). New York: Guilford Press.

Cleeremans, A. (1997). Principles for implicit learning. In D. Berry (Ed.), How implicit is implicit learning? (pp. 195–234). Oxford: Oxford University Press.

Cleeremans, A., A. Destrebecqz & M. Boyer. (1998). Implicit learning: News from the front. Trends in Cognitive Sciences, 2(10), 406–416.

Cleeremans, A. and J. McClelland, (1991). Learning the structure of event sequences. Journal of Experimental Psychology: General, 120, 235–253.

Collins, A. (1978). Fragments of a theory of human plausible reasoning. In D. Waltz (Ed.), Theoretical Issues in Natural Language Processing II, 194–201. Norword, NJ: Ablex.

Collins, A. & Loftus, J. (1975). Spreading activation theory of semantic processing. Psychological Review, 82, 407–428.

Collins, A. & Michalski, R. (1989). The logic of plausible reasoning. Cognitive Science, 13(1), 1–49.

Collins, A. M., & Quillian, M. R. (1969). Retrieval time from semantic memory. Journal of Verbal Behavior and Verbal Learning, 8, 432–438.

Cooper, R. P. (2007). The role of falsification in the development of cognitive architectures: Insights from a Lakatosian analysis. Cognitive Science, 31, 509–533.

Cosmides, L. & Tooby, L. (1994). Beyond intuition and instinct blindness: Toward an evolutionarily rigorous cognitive science. Cognition, 50, 41–77.

Curran, T. & Keele, S. (1993). Attention and structure in sequence learning. Journal of Experimental Psychology: Learning, Memory, and Cognition, 19, 189–202. (p.409)

Dai, D. Y. & Sun, R. (2012). Where is the unity of attention, representation, and performance? In S. Masmoudi, D. Y. Dai, & A. Naceur (Eds.), Attention, representation, and human performance: Integration of cognition, emotion, and motivation (pp. 217–233). London: Taylor & Francis.

Damasio, A. (1994). Descartes’ error: Emotion, reason and the human brain. New York: Grosset/Putnam.

D’Andrade, R.G. & Strauss, C. (Eds.). (1992). Human motives and cultural models. Cambridge, UK: Cambridge University Press.

Deci, E. (1980). Intrinsic motivation and personality. In E. Staub (Ed.), Personality: Basic issues and current research (pp. 35–80). Englewood Cliffs, NJ: Prentice Hall.

Deci, E. L. & Ryan, R. M. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American Psychologist, 55, 68–78.

de Quervain, D.J., Fischbacher, U., Treyer, V., Schellhammer, M., Schnyder, U., Buck, A., and Fehr, E. (2004). The neural basis of altruistic punishment. Science, 305, 1254–1258.

Dewey, J. (1958). Experience and nature. New York: Dover.

Dienes, Z. and Fahey, R. (1995). Role of specific instances in controlling a dynamic system. Journal of Experimental Psychology: Learning, Memory, and Cognition, 21(4), 848–862.

Digman, J. M. (1990). Personality structure: Emergence of the five-factor model. Annual Review of Psychology, 41, 417–440.

Doerner, D. (2003). The mathematics of emotions. In F. Detje, D. Doerner, and H. Schaub (Eds.), Proceedings of the Fifth International Conference on Cognitive Modeling (pp. 75–79). Bamberg, Germany.

Domangue, T. J., Mathews, R. C., Sun, R., Roussel, L. G., & Guidry, C. E. (2004). Effects of model-based and memory-based processing on speed and accuracy of grammar string generation. Journal of Experimental Psychology: Learning, Memory, and Cognition, 30(5), 1002–1011.

Dominowski, R. (1972). How do people discover concepts? In R. L. Solso (Ed.), Theories in cognitive psychology: The Loyola symposium (pp. 257–288). Potomac, MD: Lawrence Erlbaum Associates.

Doran, J., Palmer, M., Gilbert, N., and Mellars, P. (1994). The EOS project: Modeling upper Paleolithic social change. In N. Gilbert and J. Doran (Eds.), Simulating Societies (pp. 195–221). London: UCL Press.

Dreyfus, H. (1992). Being-in-the-world. Cambridge, MA: MIT Press.

Dreyfus, H. & Dreyfus, S. (1987). Mind over machine: The power of human intuition. New York: Free Press.

Dunn, J. & Kirsner, K. (1988). Discovering functionally independent mental processes: the principle of reversed associations. Psychological Review, 95, 21–101. (p.410)

Durkheim, W. (1962). The rules of the sociological method. Glencoe, IL: Free Press. (Original work published in 1895.)

Dweck, C. S. (2008). Can personality be changed? The role of beliefs in personality and change. Current Directions in Psychological Science, 17(6), 391–394.

Ekman, P. (1999). Basic emotions. In Dalgleish, T. & Power, M. (Eds.), Handbook of cognition and emotion. Chichester, UK: John Wiley and Sons.

Eliasmith, C. (2013). How to build a brain: A neural architecture for biological cognition. New York: Oxford University Press.

Elliot, A. & Thrash, T. (2002). Approach-avoidance motivation in personality: Approach and avoidance temperaments and goals. Journal of Personality and Social Psychology, 82(5), 804–818.

Epstein, A. (1982). Instinct and motivation as explanations for complex behavior. In D. W. Pfaff (Ed.), The physiological mechanisms of motivation. Berlin: SpringerVerlag.

Erickson, M. & Kruschke, J. (1998). Rules and exemplars in category learning. Journal of Experimental Psychology: General, 127, 107–140.

Estes, W. (1986). Memory storage and retrieval processes in category learning. Journal of Experimental Psychology: General, 115, 155–174.

Evans, J. (2003). In two minds: Dual-process accounts of reasoning. Trends in Cognitive Sciences, 7(10), 454–459.

Evans, J. & Frankish, K. (Eds.). (2009). In two minds: Dual processes and beyond. Oxford: Oxford University Press.

Fehr, E. & Gintis, H. (2007). Human motivation and social cooperation: Experimental and analytical foundations. Annual Review of Sociology, 33, 43–64.

Flavell, J. (1976). Metacognitive aspects of problem solving. In B. Resnick (Ed.), The nature of intelligence. Hillsdale, NJ: Erlbaum Associates.

Fodor, J. (1983). The modularity of mind. Cambridge, MA: MIT Press.

Foot, P. (1967). The problem of abortion and the doctrine of double effect. Oxford Review, 5, 5–15.

Frijda, N. (1986). The emotions. New York: Cambridge University Press.

Fum, D., Del Missier, F., & Stocco, A. (2007). The cognitive modeling of human behavior: Why a model is (sometimes) better than 10,000 words. Cognitive Systems Research, 8, 135–142.

Fum, D. & Stocco, A. (2003). Instance vs. rule based learning in controlling a dynamic system. In Proceeedings of the Fifth International Conference on Cognitive Modelling (pp. 105–110). Bamberg, Germany.

Gagne, R. & Smith, E. (1962). A study of the effects of verbalization on problem solving. Journal of Experimental Psychology, 63, 12–18.

Garnham, A. & Oakhill, J.V. (1994). Thinking and reasoning. Oxford: Blackwell.

Gathercole, S. (2003). Short-term and working memory. London: Taylor and Francis. (p.411)

Gentner, D., & Collins, A. (1981). Studies of inference from lack of knowledge. Memory and Cognition, 9, 434–443.

Gick, M. & Holyoak, K. (1980). Analogical problem solving. Cognitive Psychology, 12, 306–355.

Giddens, A. (1984). The constitution of society. Cambridge, UK: Polity Press.

Gigerenzer, G., Todd, P. M., & ABC Group. (1999). Simple heuristics that make us smart. New York: Oxford University Press.

Gilbert, N. (1997). A simulation of the structure of academic science. Sociological Research Online, 2(2). http://www.socresonline.org.uk/socresonline/2/2/3.html.

Gilbert, N., den Besten, M., Bontovics, A., Craenen, B. G. W., Divina, F., Eiben, A. E. (2006). Emerging artificial societies through learning. Journal of Artificial Societies and Social Simulation, 9(2). http://jasss.soc.surrey.ac.uk/9/2/9.html.

Gilbert, N. & Doran, J. (1994). Simulating societies: The computer simulation of social phenomena. London: UCL Press.

Glenberg, A., Wilkinson, A., and Epstein, W. (1982). The illusion of knowing: Failure in the self assessment of comprehension. Memory and Cognition, 10, 597–602.

Goel, V., Bruchel, C., Frith C., & Dolan, R. (2000). Dissociation of mechanisms underlying syllogistic reasoning. Neuroimage, 12(5), 504–514.

Gratch, J., & Marsella, S. (2004). A domain-independent framework for modeling emotion. Cognitive Systems Research, 5(4), 269–306.

Gray, J. A. (1987). Perspectives on anxiety and impulsivity: A commentary. Journal of Research in Personality, 21(4), 493–509.

Gray, J. A. & McNaughton, N. (2000). The neuropsychology of anxiety: An enquiry into the functions of the septo-hippocampal system (2d ed.). New York: Oxford University Press.

Greene, J. D., Cushman, F. A., Stewart, L. E., Lowenberg, K., Nystrom, L. E., & Cohen, J. D. (2009). Pushing moral buttons: The interaction between personal force and intention in moral judgment. Cognition, 111(3), 364–371.

Greene, J., Morelli, S., Lowenberg, K., Nystrom, L., & Cohen, J. (2008). Cognitive load selectively interferes with utilitarian moral judgment. Cognition, 107(3), 1144–1154.

Gross, J. J. (Ed.). (2007). Handbook of emotion regulation. New York: Guilford Press.

Grossberg, S. (1976), Adaptive pattern classification and universal recoding: I. parallel development and coding of neural feature detectors. Biological Cybernetics, 23, 121–134.

Grossberg, S. (1982). Studies of mind and brain: Neural principles of learning, perception, development, cognition, and motor control. Norwell, MA: Kluwer Academic Publishers. (p.412)

Grossberg, S. (1988). Nonlinear neural networks: Principles, mechanisms, and architectures. Neural Networks, 1, 17–61.

Gyurak, A., Gross, J. J., & A. Etkin. (2011). Explicit and implicit emotion regulation: A dual-process framework. Cognition and Emotion, 25(3), 400–412.

Hardy, L. & Parfitt, G. (1991). A catastrophe model of anxiety and performance. British Journal of Psychology, 82(2), 163–178.

Harnad, S. (1990). The symbol grounding problem. Physica D: Nonlinear phenomena, 42, 335–346.

Hasher, J. & Zacks, J. (1979). Automatic and effortful processes in memory. Journal of Experimental Psychology: General, 108, 356–358.

Heidegger, M. (1927). Being and time. New York: Harper and Row, 1962.

Heit, E. (2008). Models of inductive reasoning. In R. Sun (Ed.), Cambridge handbook of computational psychology (pp. 322–338). New York: Cambridge University Press.

Helie, S., Chartier, S., & Proulx, R. (2006). Are unsupervised neural networks ignorant? Sizing the effect of environmental distributions on unsupervised learning. Cognitive Systems Research, 7, 357–371.

Helie, S., Roeder, J. L., & Ashby, F. G. (2010). Evidence for cortical automaticity in rule-based categorization. Journal of Neuroscience, 30(42), 14225–14234.

Helie, S., Proulx, R., & Lefebvre, B. (2011). Bottom-up learning of explicit knowledge using a Bayesian algorithm and a new Hebbian learning rule. Neural Networks, 24(3), 219–232.

Helie, S. & Sun, R. (2010). Incubation, insight, and creative problem solving: A unified theory and a connectionist model. Psychological Review, 117(3), 994–1024.

Helie, S. & Sun, R. (2010b). Creative problem solving: A Clarion theory. Proceedings of the 2010 International Joint Conference on Neural Networks, Barcelona, Spain. pp. 1460–1466. Piscataway, NJ: IEEE Press.

Helie, S. & Sun, R. (2014). An integrative account of memory and reasoning phenomena. New Ideas in Psychology, 35, 36–52.

Helie, S. & Sun, R. (2014b). Autonomous learning in psychologically-oriented cognitive architectures: A survey. New Ideas in Psychology, 34, 37–55.

Henrich, J., Heine, S. J., & Norenzayan, A. (2010). Beyond WEIRD: Towards a broad-based behavioral science. Behavioral and Brain Sciences, 33(2–3), 111–135.

Higgins E. T. (1997). Beyond pleasure and pain. American Psychologist, 52(12), 1280–1300.

Hintzman, D. (1990). Human learning and memory: Connections and dissociations. Annual Review of Psychology, 41, 109–139.

Hopfield, J. J. (1982). Neural networks and physical systems with emergent collective computational abilities. Proceedings of the National Academy of Sciences, 79, 2554–2558. (p.413)

Huang, J. & Bargh, J. (2014). The selfish goal: Autonomously operating motivational structures as the proximate cause of human judgment and behavior. Behavioral and Brain Sciences, 37, 121–175.

Hull, C. (1943). Principles of behavior: An introduction to behavior theory. New York: D. Appleton-Century Company.

Hull, C. (1951). Essentials of behavior. New Haven, CT: Yale University Press.

Humphreys, M. S. & Revelle, W. (1984). Personality, motivation, and performance: A theory of the relationship between individual differences and information processing. Psychological Review, 91(2), 153–184.

Jacoby, L. (1983). Perceptual enhancement: persistent effects of an experience. Journal of Experimental Psychology: Learning, Memory, and Cognition, 9(1), 21–38.

James, W. (1890). The principles of psychology. New York: Dover.

John, O. P. & Srivastava, S., (1999). The Big Five trait taxonomy: history, measurement, and theoretical perspectives. In L. A. Pervin & O. P. John (Eds.), Handbook of personality: Theory and research (2nd edition) (pp. 102–138). New York: Guilford Press.

Johnson, M. (1987). The body in the mind: The bodily basis of imagination, reason, and meaning. Chicago: University of Chicago Press.

Johnson, T. (1998). Acquisition and transfer of declarative and procedural knowledge. Proceedings of the European Conference on Cognitive Modeling (pp. 15–22). Nottingham, UK: Nottingham University Press.

Johnson-Laird, P.N., and Yang, Y., (2008). Mental logic, mental models, and computer simulations of human reasoning. In R. Sun (Ed.), Cambridge handbook of computational psychology. New York: Cambridge University Press.

Kahneman, D. (2003). A perspective on judgment and choice: Mapping bounded rationality. American Psychologist, 58(9), 697–720.

Kanfer, R. & Ackerman, P. L. (1989). Motivation and cognitive abilities: An integrative/aptitude-treatment interaction approach to skill acquisition. Journal of Applied Psychology, 74(4), 657–690.

Karmiloff-Smith, A. (1986). From meta-processes to conscious access: Evidence from children’s metalinguistic and repair data. Cognition, 23, 95–147.

Keil, F. (1989). Concepts, kinds, and cognitive development. Cambridge, MA: MIT Press.

Kennedy, W. G., & Bugajska, M. (2010). Integrating fast and slow cognitive processes. In D.D. Salvucci & G. Gunzelmann (Eds.), Proceedings of the International Conference on Cognitive Modeling (ICCM 2010) (pp. 121–126). Philadelphia, PA: Drexel University.

Kent, G. H., & Rosanoff, A. J. (1910). A study of association in insanity. American Journal of Psychiatry, 67, 317–390.

Kirsh, D. (1990). When is information explicitly represented. In P. Hanson (Ed.), Information, language, and cognition. Vancouver: University of British Columbia Press. (p.414)

Klein, S., Cosmides, L., Tooby, J., and Chance, S. (2002). Decisions and the evolution of memory: Multiple systems, multiple functions. Psychological Review, 109(2), 306–329.

Kluver, J., Schmidt, J., & Stoica, C. (2005). The emergence of social order by processes of typifying: A computational model. Journal of Mathematical Sociology, 29, 155–176.

Koch, C. (2011 March/April). Being John Malkovich. Scientific American Mind, 18–19.

Kuhn, T. (1970). Structure of scientific revolutions. Chicago: University of Chicago Press.

Laird, J. (2012). The Soar cognitive architecture. Cambridge, MA: MIT Press.

Lakatos, I. (1970). Falsification and methodology of research programs. In I. Lakatos & A. Musgrave (Eds.), Criticism and the growth of knowledge. Cambridge, UK: Cambridge University Press.

Lambert, A., Payne, B., Jacoby, L., Shaffer, L., Chasteen, A., & Khan, S. (2003). Stereotypes as dominant responses: On the “social facilitation” of prejudice in anticipated public contexts. Journal of Personality and Social Psychology, 84(2), 277–295.

Lane, S., Mathews, R., Sallas, B., Prattini, R., & Sun, R. (2008). Facilitative interactions of model- and experience-based processes: Implications for type and flexibility of representation. Memory and Cognition, 36(1), 157–169.

Langley, P. A., Laird, J. E. B., & Rogers, S.A. (2009). Cognitive architectures: Research issues and challenges. Cognitive Systems Research, 10(2), 141–160.

Lavrac, N. & Dzeroski, S. (1994). Inductive logic programming. New York: Ellis Horword.

Lazarus, R. S., & Folkman, S. (1984). Stress, appraisal, and coping. New York: Springer.

LeDoux, J. (1996). The emotional brain. New York: Simon and Schuster.

Leven, S. & Levine, D. S. (1996). Multi-attribute decision making in context: A dynamic neural network methodology. Cognitive Science, 20, 271–299.

Levine, D. S. (2000). Introduction to neural and cognitive modeling. Mahwah, NJ: Erlbaum Associates.

Lewicki, P. (1986). Processing information about covariations that cannot be articulated. Journal of Experimental Psychology: Learning, Memory, and Cognition, 12, 135–146.

Lewicki, P., Czyzewska, M., & Hoffman, H. (1987). Unconscious acquisition of complex procedural knowledge. Journal of Experimental Psychology: Learning, Memory and Cognition, 13(4), 523–530.

Lewis, B. & Linder, D. (1997). Thinking about choking: Attentional processes and paradoxical performance. Personality and Social Psychology Bulletin, 23, 937–944. (p.415)

Li, M., & Vitanyi, P. (1997). An introduction to Kolmogorov complexity and its applications. Heidelberg, Germany: Springer.

Libet, B. (1985). Unconscious cerebral initiative and the role of conscious will in voluntary action. Behavioral and Brain Sciences, 8, 529–566.

Licato, J., Sun, R., & Bringsjord, S. (2014). Using a hybrid cognitive architecture to model children’s errors in an analogy task. Proceedings of the Annual Conference of Cognitive Science Society, Quebec City, Quebec. (pp. 857–862). Austin, TX: Cognitive Science Society.

Licato, J., Sun, R., & Bringsjord, S. (2014b). Structural representation and reasoning in a hybrid cognitive architecture. Proceedings of the 2014 International Joint Conference on Neural Networks. Piscataway, NJ: IEEE Press.

Licklider, J. C. R. (1960). Man-computer symbiosis. IRE Transactions on Human Factors in Electronics, HFE-1, 4–11.

Lieberman, M. D. (2009). What zombies can’t do: A social cognitive neuroscience approach to the irreducibility of reflective consciousness. In J. St. B. T. Evans & K. Frankish (Eds.), In two minds: Dual processes and beyond (pp. 293–316). Oxford: Oxford University Press.

Locke, E. A. & Latham, G. P. (1990). A theory of goal setting and task performance. Englewood Cliffs, NJ: Prentice Hall,

Locke, E. A. & Latham, G. P. (2002). Building a practically useful theory of goal setting and task motivation: A 35-year odyssey. American Psychologist, 57(9), 705–717.

Logan, G. (1988). Toward an instance theory of automatization. Psychological Review, 95(4), 492–527.

López, F. J. & Shanks, D. R. (2008). Models of animal learning and their relations to human learning. In R. Sun (Ed.), Cambridge handbook of computational psychology. New York: Cambridge University Press.

Lotka, A. J. (1926). The frequency distribution of scientific productivity. Journal of the Washington Academy of Sciences, 16, 317–323.

Luce, R. D. (1959). Individual choice behavior: A theoretical analysis. New York: Wiley.

Lustick, I. (2000). Agent-based modeling of collective identity: Testing constructivist theory. Journal of Artificial Society and Social Simulation, 3(1). http://www.soc.surrey.ac.uk/JASSS/3/1/1.html

Mandler, J. (1992). How to build a baby. Psychological Review, 99(4), 587–604.

Maner, J. K., Kenrick, D. T., Neuberg, S. L., Becker, D. V., Robertson, T., Hofer, B., … Schaller, M. (2005). Functional projection: How fundamental social motives can bias interpersonal perception. Journal of Personality and Social Psychology, 88, 63–78.

Marcel, A. J. (1983). Conscious and unconscious perception: An approach to the relations between phenomenal experience and perceptual processes. Cognitive Psychology, 15, 238–300. (p.416)

Marinier, R. P., Laird, J. E., & Lewis, R. L. (2009). A computational unification of cognitive behavior and emotion. Cognitive Systems Research, 10(1), 48–69.

Markman, A. B. & Maddox, W. T. (2005). The implications of advances in research on motivation for cognitive models. Journal of Experimental and Theoretical Artificial Intelligence, 17, 371–384.

Marr, D. (1982). Vision: A computational investigation into the human representation and processing of visual information. New York: W. H. Freeman.

Marsella, S. & Gratch, J. (2009). EMA: A process model of appraisal dynamics. Cognitive Systems Research, 10(1), 70–90.

Maslow, A. (1943). A theory of human motivation. Psychological Review, 50, 370–396.

Maslow, A. (1987). Motivation and personality. 3d ed. New York: Harper and Row.

Masmoudi, S., D. Y. Dai, & A. Naceur (Eds.). (2012). Attention, representation, and human performance: Integration of cognition, emotion, and motivation. London: Taylor & Francis.

Massaro, D. (1988). Some criticisms of connectionist models of human performance. Journal of Memory and Language, 27, 213–234.

Mathews, R., Buss, R., Stanley, W., Blanchard-Fields, F., Cho, J., & Druhan, B. (1989). Role of implicit and explicit processes in learning from examples: A synergistic effect. Journal of Experimental Psychology: Learning, Memory and Cognition. 15, 1083–1100.

Mathews, R., Tall, J., Lane, S. M., & Sun, R. (2011). Getting it right generally, but not precisely: Learning the relation between multiple inputs and outputs. Memory and Cognition, 39(6), 1133–1145.

Mayer, J. D. (2005). Tale of two visions: Can a new view of personality help integrate psychology? American Psychologist, 60(4), 294–307.

Mazzoni, G. & T. Nelson (Eds.). (1998). Metacognition and cognitive neuropsychology. Mahwah, NJ: Erlbaum Associates.

McClelland, J., McNaughton, B., & O’Reilly, R. (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(3), 419–457.

McCrae, R. R. (2002). Cross-cultural research on the five-factor model of personality. In W. J. Lonner, D. L. Dinnel, S. A. Hayes, & D. N. Sattler (Eds.), Online readings in psychology and culture. Bellingham, WA: Center for Cross-Cultural Research, Western Washington University.

McCrae, R. R., & Costa, P. T. Jr. (2010). NEO inventories: Professional manual. Lutz, FL: Psychological Assessment Resources.

McDougall, W. (1936). An introduction to social psychology. London: Methuen & Co. (p.417)

McFarland, D. (1989). Problems of animal behaviour. New York: Longman.

Merikle, P. M., & Daneman, M. (1998). Psychological investigations of unconscious perception. Journal of Consciousness Studies, 5, 5–18.

Merleau-Ponty, M. (1963). The structure of behavior. Boston: Beacon Press.

Metcalfe, J. (1986). Dynamic metacognitive monitoring during problem solving. Journal of Experimental Psychology: Learning, Memory and Cognition, 12, 623–634.

Meyer, D. & Kieras, D. (1997). A computational theory of executive cognitive processes and human multiple-task performance: Part 1, basic mechanisms. Psychological Review, 104(1), 3–65.

Miikkulainen, R. (1993). Subsymbolic natural language processing: An integrated model of scripts, lexicon, and memory. Cambridge, MA: MIT Press.

Mikhail, J. (2007). Universal moral grammar: Theory, evidence and the future. Trends in Cognitive Sciences, 11(4), 143–152.

Miller, G. A. (1956). The magical number seven, plus or minus two: Some limits on our capacity for processing information. Psychological Review, 63, 81–97.

Miller, G. A., Galanter, E., & Pribram, K. H. (1960). Plans and the structure of behavior. New York: Holt.

Milner, D., and Goodale, M. (1995). The visual brain in action. Oxford: Oxford University Press.

Mineka, S. & Sutton, S. (1992). Cognitive biases and the emotional disorders. Psychological Science, 3(1), 65–69.

Minsky, M. (1985). The society of mind. New York: Simon and Schuster.

Monroe, K. (2012). Cognition and moral choice. In R. Sun (Ed.), Grounding social sciences in cognitive sciences (pp.183–206). Cambridge, MA: MIT Press.

Montague, P. R. (1999). Review of reinforcement learning: An introduction. Trends in Cognitive Science, 3(9), 360–361.

Montgomery, K. J., Seeherman, K. R., & Haxby, J. V. (2009). The well-tempered social brain. Psychological Science, 20(10), 1211–1213.

Moscovitch, M. & Umilta, C. (1991). Conscious and unconscious aspects of memory: A neuropsychological framework of modules and central systems. In R. Lister & H. Weingartner (Eds.), Perspectives on cognitive neuroscience. New York: Oxford University Press.

Moskowitz, D. S., Suh, E. J., and Desaulniers, J. (1994). Situational influences on gender differences in agency and communion. Journal of Personality and Social Psychology, 66, 753–761.

Murray, H. (1938). Explorations in personality. New York: Oxford University Press.

Naveh, I. and Sun, R. (2006). A cognitively based simulation of academic science. Computational and Mathematical Organization Theory, 12(4), 313–337. (p.418)

Nelson, D., McKinney, V., Gee, N., and Janczura, G. (1998). Interpreting the influence of implicitly activated memories on recall and recognition. Psychological Review, 105(2), 299–324.

Newell, A. (1990). Unified theories of cognition. Cambridge, MA: Harvard University Press.

Newell, A., & Simon, H. A. (1972). Human problem solving. Englewood Cliffs, NJ: Prentice-Hall.

Newell, A., & Simon, H. A. (1976). Computer science as empirical inquiry: Symbols and search. Communications of the ACM, 19(3), 113–126.

Nisbett, R. & Wilson, T. (1977). Telling more than we can know: Verbal reports on mental processes. Psychological Review, 84(3), 231–259.

Nokes, T. J., & Ohlsson, S. (2001). How is abstract generative knowledge acquired? A comparison of three learning scenarios. In J. D. Moore and K. Stenning (Eds.), Proceedings of the Twenty Third Annual Conference of the Cognitive Science Society (pp. 710–715). Mahwah, NJ: Erlbaum Associates.

Norman, D. & Shallice, T. (1986). Attention to action: Willed and automatic control of behavior. In G. Schwartz & D. Shapiro (Eds.), Consciousness and self regulation: Advances in research and theory (pp. 1–18). New York: Plenum.

Norman, K., Detre, G., & Polyn, S. (2008). Computational models of episodic memory. In R. Sun (Ed.), Cambridge handbook on computational psychology (pp. 189–225). New York: Cambridge University Press.

Norton, M., Vandello, J., & Darley, J. (2004). Casuistry and social category bias. Journal of Personality and Social Psychology, 87(6), 817–831.

O’Reilly, R. C. & Munakata, Y. (2000). Computational explorations in cognitive neuroscience: Understanding the mind by simulating the brain. Cambridge, MA: MIT Press.

Ortony, A., Clore, G., & Collins, A. (1988). The cognitive structure of emotions. Cambridge, UK: Cambridge University Press.

Osherson, D.N., Smith, E. E., Wilkie, O., Lopez, A., & Shafir, E. (1990). Category-based induction. Psychological Review, 97, 185–200.

Osman, M. (2010). Controlling uncertainty: A review of human behavior in complex dynamic environments. Psychological Bulletin, 136(1), 65–86.

Over, H. & Carpenter, M. (2009). Eighteen-month-old infants show increased helping following priming with affiliation. Psychological Science, 20, 1189–1193.

Pew, R. W. & Mavor, A. S. (Eds.). (1998). Modeling human and organizational behavior: Application to military simulations. Washington, DC: National Academy Press.

Posner, M., DiGirolamo, G., & Fernandez-Duque, D. (1997). Brain mechanisms of cognitive skills. Consciousness and Cognition, 6, 267–290.

Proctor, R. & Dutta, A. (1995). Skill acquisition and human performance. Thousand Oaks, CA: SAGE. (p.419)

Quek, M., & Moskowitz, D. S. (2007). Testing neural network models of personality. Journal of Research in Personality, 41, 700–706.

Quillian, M. R. (1968). Semantic memory. In M. Minsky (Ed.), Semantic information processing (pp. 227–270). Cambridge, MA: MIT Press.

Rabinowitz, M. & Goldberg, N. (1995). Evaluating the structure-process hypothesis. In F. Weinert & W. Schneider (Eds.), Memory performance and competencies. Hillsdale, NJ: Lawrence Erlbaum Associates.

Rao, A. S. & Georgeff, M. P. (1991). Modeling rational agents within a BDI-architecture. In J. Allen, R. Fikes, & E. Sandewall (Eds.), Proceedings of the 2nd International Conference on Principles of Knowledge Representation and Reasoning (pp. 473–484). San Mateo: Morgan Kaufmann Publishers.

Read, S. J., Monroe, B. M., Brownstein, A. L., Yang, Y., Chopra, G., and Miller, L. C. (2010). Virtual personalities II: A neural network model of the structure and dynamics of human personality. Psychological Review, 117, 61–92.

Reber, A. (1989). Implicit learning and tacit knowledge. Journal of Experimental Psychology: General, 118(3), 219–235.

Reber, A. & Allen, R. (1978). Analogy and abstraction strategies in synthetic grammar learning: A functionalist interpretation. Cognition, 6, 189–221.

Reber, A., Kassin, S., Lewis, S., & Cantor, G. (1980). On the relationship between implicit and explicit modes in the learning of a complex rule structure. Journal of Experimental Psychology: Human Learning and Memory, 6, 492–502.

Reber, A. & Lewis, S. (1977). Toward a theory of implicit learning: The analysis of the form and structure of a body of tacit knowledge. Cognition, 5, 333–361.

Reder, L. (Ed.). (1996). Implicit memory and metacognition. Mahwah, NJ: Erlbaum Associates.

Reder, L. & Schunn, C. (1996). Metacognition does not imply awareness: Strategy choice is governed by implicit learning and memory. In L. Reder (Ed.), Implicit memory and metacognition. Mahwah, NJ: Erlbaum Associates.

Reisenzein, R. (2009). Emotions as metarepresentational states of mind: Naturalizing the belief-desire theory of emotion. Cognitive Systems Research, 10(1), 6–20.

Reiss, S. (2004). Multifaceted nature of intrinsic motivation: The theory of 16 basic desires. Review of General Psychology, 8(3), 179–193.

Reiss, S. (2008). The normal personality: A new way of thinking about people. New York: Cambridge University Press.

Reynolds, R. (1994). Learning to co-operate using cultural algorithms. In N. Gilbert and J. Doran (Eds.), Simulating societies: The computer simulation of social phenomena. London: UCL Press.

Rips, L. J. (1975). Inductive judgments about mental categories. Journal of Verbal Learning and Verbal Behavior, 14, 665–681. (p.420)

Rips, L. (1994). The psychology of proof. Cambridge, MA: MIT Press.

Ritter, F. E. & Bibby, P. A. (2008). Modeling how, when, and what is learned in a simple fault-finding task. Cognitive Science, 32(5), 862–892.

Ritter, F., Shadbolt, N., Elliman, D., Young, R., Gobet, F., & Baxter, G. (2003). Techniques for modeling human performance in synthetic environments: A supplementary review. Dayton, OH: Human Systems Information Analysis Center, Wright-Patterson Air Force Base.

Roberts, S. & Pashler, H. (2000). How persuasive is a good fit? A comment on theory testing. Psychological Review, 107(2), 358–367.

Roediger, H. (1990). Implicit memory: Retention without remembering. American Psychologist, 45(9), 1043–1056.

Rogers, T. (2008). Computational models of semantic memory. In R. Sun (Ed.), Cambridge handbook on computational psychology (pp. 226–266). New York: Cambridge University Press.

Rosenbaum, D., Carlson, R., & Gilmore, R. (2001). Acquisition of intellectual and perceptual-motor skills. Annual Review of Psychology, 52, 453–470.

Rosenbloom, P., Laird, J., & Newell, A. (1993). The SOAR papers: Research on integrated intelligence. Cambridge, MA: MIT Press.

Rumelhart, D., McClelland, J., & PDP Research Group. (1986). Parallel distributed processing: Explorations in the microstructures of cognition. Cambridge, MA: MIT Press.

Samuel, D.B., & Widiger, T.A. (2008). A meta-analytic review of the relationships between the five-factor model and DSM-IV-TR personality disorders: A facet level analysis. Clinical Psychology Review, 28(8), 1326–1342.

Sawyer, K. (2003). Artificial societies: Multiagent systems and the micro-macro link in sociological theory. Sociological Methods & Research, 31(3), 325–363.

Schacter, D. (1987). Implicit memory: History and current status. Journal of Experimental Psychology: Learning, Memory, and Cognition, 13, 501–518.

Schacter, D. (1990). Toward a cognitive neuropsychology of awareness: Implicit knowledge and anosagnosia. Journal of Clinical and Experimental Neuropsychology, 12(1), 155–178.

Schelling, T. C. (1971). Dynamic models of segregation. Journal of Mathematical Sociology, 1, 143–186.

Schmidhuber, J. (2014). Deep learning in neural networks: An Overview. http://www.idsia.ch/~juergen/deep-learning-overview.html.

Schooler, J. W., Ohlsson, S., & Brooks, K. (1993). Thoughts beyond words: When language overshadows insight. Journal of Experimental Psychology: General, 122, 166–183.

Schopenhauer, A. (1819). The world as will and representation. Translated by E. F. J. Payne. New York: Dover Publications, 1969.

Schutz, A. (1967). The phenomenology of the social world. Evanston, IL: Northwestern University Press. (p.421)

Schwartz, S. (1994). Are there universal aspects of human values? Journal of Social Issues, 50, 19–45.

Seger, C. (1994). Implicit learning. Psychological Bulletin, 115(2), 163–196.

Shanks, D. & St. John, M. (1994). Characteristics of dissociable learning systems. Behavioral and Brain Sciences, 17, 367–394.

Sheldon, K. M. (2011). Integrating behavioral-motive and experiential- requirement perspectives on psychological needs: A two process model. Psychological Review, 118(4), 552–569.

Shoda, Y., & Mischel, W. (1998). Personality as a stable cognitive–affective activationnetwork: Characteristic patterns of behavior variation emerge from a stable personality structure. In S. J. Read & L. C. Miller (Eds.), Connectionist models of social reasoning and social behavior (pp. 175–208). Mahwah, NJ: Lawrence Erlbaum Associates.

Shultz, T. R., & Sirois, S. (2008). Computational models of developmental psychology. In R. Sun (Ed.), The Cambridge handbook of computational psychology (pp. 451–476). New York: Cambridge University Press.

Siegler, R. & Stern, E. (1998). Conscious and unconscious strategy discovery: A microgenetic analysis. Journal of Experimental Psychology: General, 127(4), 377–397.

Simon, H.A. (1957). Models of man, social and rational. New York: Wiley.

Simon, H. A. (1967). Motivational and emotional controls of cognition. Psychological Review, 74, 29–39.

Sloman, S. (1993). Feature based induction. Cognitive Psychology, 25, 231–280.

Sloman, S. (1996). The empirical case for two systems of reasoning. Psychological Bulletin, 119, 3–22.

Sloman, S. (1998). Categorical inference is not a tree: The myth of inheritance hierarchies. Cognitive Psychology, 35, 1–33.

Smillie, L. D., Pickering, A. D., & Jackson, C. J. (2006). The new Reinforcement Sensitivity Theory: Implications for personality measurement. Personality and Social Psychology Review, 10, 320–335.

Smith, C. A., & Lazarus, R. (1990). Emotion and adaptation. In L. A. Pervin (Ed.), Handbook of personality: Theory & research (pp. 609–637). New York: Guilford Press.

Smith, E. & Medin, D. (1981). Categories and concepts. Cambridge, MA: Harvard University Press.

Smolensky. P. (1988). On the proper treatment of connectionism, Behavioral and Brain Sciences, 11, 1–43.

Squire, L. (1987). Memory and brain. New York: Oxford University Press.

Squire, L., & Frambach, M. (1990). Cognitive skill learning in amnesia. Psychobiology, 18, 109–117.

Stadler, M. A. (1995). Role of attention in implicit learning. Journal of Experimental Psychology: Learning, Memory, and Cognition, 21, 674–685. (p.422)

Stadler, M. & Frensch, P. (1998). Handbook of implicit learning. Thousand Oaks, CA: SAGE.

Stanley, W., Mathews, R., Buss, R., & Kotler-Cope, S. (1989). Insight without awareness: On the interaction of verbalization, instruction and practice in a simulated process control task. Quarterly Journal of Experimental Psychology. 41A (3), 553–577.

Strack, F. & Deutsch, R. (2005). Reflection and impulse as determinants of conscious and unconscious motivation. In J. Forgas, K. Williams, and S. Laham (Eds.), Social motivation: Conscious and unconscious processes. New York: Cambridge University Press.

Suh, E. J., D. S.Moskowitz, M. Fournier, and D. C. Zuroff (2004). Gender and relationships: Influences on agentic and communal behaviors. Personal Relationships, 11, 41–59.

Sun, R. (1991). Connectionist models of rule-based reasoning. Proceedings of the 13th Cognitive Science Conference (pp. 437–442). Hillsdale, NJ: Lawrence Erlbaum Associates.

Sun, R. (1993). An efficient feature-based connectionist inheritance scheme. IEEE Transactions on System, Man, and Cybernetics, 23(1), 23–54.

Sun, R. (1994). Integrating rules and connectionism for robust commonsense reasoning. New York: Wiley.

Sun, R. (1995). Robust reasoning: Integrating rule-based and similarity-based reasoning. Artificial Intelligence, 75(2), 241–296.

Sun, R. (1995b). A microfeature-based approach toward metaphor interpretation. Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI-95) (pp. 424–430). San Francisco, CA: Morgan Kaufmann.

Sun, R. (1999). Accounting for the computational basis of consciousness: A connectionist approach. Consciousness and Cognition, 8, 529–565.

Sun, R. (2000). Symbol grounding: A new look at an old issue. Philosophical Psychology, 13(3), 403–418.

Sun, R. (2001). Cognitive science meets multi-agent systems: A prolegomenon. Philosophical Psychology, 14(1), 5–28.

Sun, R. (2002). Duality of the mind. Mahwah, NJ: Lawrence Erlbaum Associates.

Sun, R. (2003). A Tutorial on Clarion 5.0. Technical report, Cognitive Sciences Department, Rensselaer Polytechnic Institute, Troy, NY. http://www.cogsci.rpi.edu/~rsun/sun.tutorial.pdf

Sun, R. (2004). Desiderata for cognitive architectures. Philosophical Psychology, 17(3), 341–373.

Sun, R. (Ed.). (2006). Cognition and multi-agent interaction. New York: Cambridge University Press.

Sun, R. (2007). The importance of cognitive architectures: An analysis based on Clarion. Journal of Experimental and Theoretical Artificial Intelligence, 19(2), 159–193. (p.423)

Sun, R. (2007b). The motivational and metacognitive control in Clarion. In W. Gray (Ed.), Integrated models of cognitive systems (pp. 63–75). New York: Oxford University Press.

Sun, R. (Ed.). (2008). The Cambridge handbook of computational psychology. New York: Cambridge University Press.

Sun, R. (2009). Motivational representations within a computational cognitive architecture. Cognitive Computation, 1(1), 91–103.

Sun, R. (2009b). Theoretical status of computational cognitive modeling. Cognitive Systems Research, 10(2), 124–140.

Sun, R. (2012). Memory systems within a cognitive architecture. New Ideas in Psychology, 30, 227–240.

Sun, R. (Ed.). (2012b). Grounding social sciences in cognitive sciences. Cambridge, MA: MIT Press.

Sun, R. (2013). Moral judgment, human motivation, and neural networks. Cognitive Computation, 5(4), 566–579.

Sun, R. (2013b). Autonomous generation of symbolic representations through subsymbolic activities. Philosophical Psychology, 26(6), 888–912.

Sun, R. (2014). Interpreting psychological notions: A dual-process computational theory. Journal of Applied Research in Memory and Cognition, in press.

Sun, R. & L. Bookman (Eds.). (1994). Computational architectures integrating neural and symbolic processes. Needham, MA: Kluwer Academic Publishers.

Sun, R., Coward, L. A., & Zenzen, M. J. (2005b). On levels of cognitive modeling. Philosophical Psychology, 18(5), 613–637.

Sun, R. & Fleischer, P. (2012). A cognitive social simulation of tribal survival strategies: The importance of cognitive and motivational factors. Journal of Cognition and Culture, 12(3–4), 287–321.

Sun, R. & Helie, S. (2012). Reasoning with heuristics and induction. Proceedings of the 2012 International Joint Conference on Neural Networks, Brisbane, Australia (pp. 1359–1366). Piscataway, NJ: IEEE Press.

Sun, R. & Helie, S. (2013). Psychologically realistic cognitive agents: Taking human cognition seriously. Journal of Experimental and Theoretical Artificial Intelligence, 25, 65–92.

Sun, R., Honavar, V., and Oden, G. (1999). Integration of cognitive systems across disciplinary boundaries. Cognitive Systems Research, 1(1), 1–3.

Sun, R. & Mathews, R. (2005). Exploring the interaction of implicit and explicit processes to facilitate individual skill learning. Technical Report TR-1162, Army Research Institute for the Social and Behavioral Sciences, Arlington, VA.

Sun, R. & R. Mathews. (2012). Implicit cognition, emotion, and meta-cognitive control. Mind and Society, 11(1), 107–119. (p.424)

Sun, R., Merrill, E., & Peterson, T. (2001). From implicit skills to explicit knowledge: A bottom-up model of skill learning. Cognitive Science, 25, 203–244.

Sun, R. & Naveh, I. (2004). Simulating organizational decision-making using a cognitively realistic agent model. Journal of Artificial Societies and Social Simulation, 7(3). http://jasss.soc.surrey.ac.uk/7/3/5.html

Sun, R. & Naveh, I. (2007). Social institution, cognition, and survival: A cognitive-social simulation. Mind and Society, 6(2), 115–142.

Sun, R. & Peterson, T. (1998). Autonomous learning of sequential tasks: Experiments and analyses. IEEE Transactions on Neural Networks, 9(6), 1217–1234.

Sun, R., Slusarz, P., & Terry, C. (2005). The interaction of the explicit and the implicit in skill learning: A dual-process approach. Psychological Review, 112(1), 159–192.

Sun, R. & Wilson, N. (2011). Motivational processes within the perception-action cycle. In V. Cutsuridis, A. Hussain, and J. G. Taylor (Eds.), Perception-action cycle: Models, architectures and hardware (pp. 449–472). Berlin: Springer.

Sun, R. & Wilson, N. (2014). Roles of implicit processes: Instinct, intuition, and personality. Mind and Society, 13(1), 109–134.

Sun, R. & Wilson, N. (2014b). A model of personality should be a cognitive architecture itself. Cognitive Systems Research, 2930, 1–30.

Sun, R., Wilson, N., & Mathews, R. (2011). Accounting for certain mental disorders within a comprehensive cognitive architecture. Cognitive Computation, 3(2), 341–359.

Sun, R. & Zhang, X. (2004). Top-down versus bottom-up learning in cognitive skill acquisition. Cognitive Systems Research, 5(1), 63–89.

Sun, R. & Zhang, X. (2006). Accounting for a variety of reasoning data within a cognitive architecture. Journal of Experimental and Theoretical Artificial Intelligence, 18(2), 169–191.

Sun, R., X. Zhang, and R. Mathews, (2006). Modeling meta-cognition in a cognitive architecture. Cognitive Systems Research, 7(4), 327–338.

Sun, R., Zhang, X., & Mathews, R. (2009). Capturing human data in a letter counting task: Accessibility and action-centeredness in representing cognitive skills. Neural Networks, 22, 15–29.

Sun, R., Zhang, X., Slusarz, P., & Mathews, R. (2007). The interaction of implicit learning, explicit hypothesis testing learning, and implicit-to-explicit knowledge extraction. Neural Networks, 20(1), 34–47.

Sutton, R. & Barto, A. (1998). Reinforcement learning. Cambridge, MA: MIT Press.

Taatgen, N. & Anderson, J. (2008). Constraints in cognitive architectures. In R. Sun (Ed.), The Cambridge handbook of computational psychology (pp. 170–185). New York: Cambridge University Press. (p.425)

Taatgen, N., & Wallach, D. (2002). Whether skill acquisition is rule or instance based is determined by the structure of the task. Cognitive Science Quarterly, 2(2), 163–204.

Tetlock, P. & Lebow, R.N. (2001). Poking counterfactual holes in covering laws: Cognitive styles and historical reasoning. American Political Science Review, 95, 829–843.

Thagard, P. (1996). Mind: Introduction to Cognitive Science. Cambridge, MA: MIT Press.

Thomson, J. J. (1985). The trolley problem. Yale Law Journal, 94, 1395–1415.

Thórisson, K. R. & Helgasson, H. P. (2012). Cognitive architectures and autonomy: A comparative review. Journal of Artificial General Intelligence, 3(2), 1–30.

Thorndike, E. (1911). Animal intelligence. Darien, CT: Hafner,

Timberlake, W. & Lucas, G. (1989). Behavior systems and learning: From misbehavior to general principles. In S. B. Klein & R. R. Mowrer (Eds.), Contemporary learning theories: Instrumental conditioning theory and the impact of biological constraints on learning (pp. 237–275). Hillsdale, NJ: Lawrence Erlbaum Associates,

Tinbergen, N. (1951). The study of instinct. London: Oxford University Press.

Toates, F. (1986). Motivational systems. Cambridge, UK: Cambridge University Press.

Tolman, E. C. (1932). Purposive behavior in animals and men. New York: Century.

Toth, J., Reingold, E., & Jacoby, L. (1994). Toward a redefinition of implicit memory: Process dissociations following elaborative processing and self-generation. Journal of Experimental Psychology: Learning, Memory, and Cognition, 20(2), 290–303.

Tsunoda, K., Yamane, Y., Nishizaki, M., & Tanifuji, M. (2001). Complex objects are represented in macaque inferotemporal cortex by the combination of feature columns. Nature Neuroscience, 4(8), 832–838.

Tulving, E. (1972). Episodic and semantic memory. In E. Tulving and W. Donaldson (Eds.), Organization of memory (pp. 381–403). New York: Academic Press.

Tulving, E. (1983). Elements of episodic memory. Oxford: Clarendon Press.

Tulving, E. (1985). How many memory systems are there? American Psychologist, 40, 385–398.

Tulving, E. and D. Schacter, (1990). Priming and human memory systems. Science, 247, 301–305.

Tversky, A. (1977). Features of similarity. Psychological Review, 84(4), 327–352.

Tversky, A. & Kahneman, D. (1974). Judgment under uncertainty: Heuristics and biases. Science, 185, 1124–1131. (p.426)

Tversky, A. & Kahneman, D. (1983). Extensional versus intuitive reasoning: The conjunction fallacy in probability judgment. Psychological Review, 90, 439–450.

Tyrell, T. (1993). Computational mechanisms for action selection. PhD thesis, Oxford University, Oxford, UK.

Vaesen, K. (2012). The cognitive bases of human tool use. Behavioral and Brain Sciences, 35(4), 203–262.

van de Vliert, E. (2013). Climato-economic habitats support patterns of human needs, stresses, and freedoms. Behavioral and Brain Sciences, 36(5), 465–480.

van Fraassen, B. (1980). The scientific image. Oxford: Oxford University Press.

Vygotsky, L. (1962). Thought and language. Cambridge, MA: MIT Press.

Warrington, E. & Weiskrantz, L. (1970). Amnesic syndrome: Consolidation or retrieval? Nature, 228, 628–630.

Watkins, C. (1989). Learning with delayed rewards. PhD thesis, Cambridge University, Cambridge, UK.

Weber, M. (1991). Weber: Selections in translation. Cambridge, UK: Cambridge University Press.

Wegener, D. T. & Petty, R. E. (2001). On the use of naive theories of bias to remove or avoid bias: the flexible correction model. In M. C. Gilly and J. Meyers-Levy (Eds.), Advances in consumer research (pp. 378–383). Valdosta, GA: Association for Consumer Research.

Wegner, D. M., & Bargh, J. A. (1998). Control and automaticity in social life. In D. Gilbert, S. T. Fiske, & G. Lindzey (Eds.), Handbook of social psychology (4th ed.) (pp. 446–496). New York: McGraw-Hill.

Wegner, D. M., & Wheatley, T. P. (1999). Apparent mental causation: Sources of the experience of will. American Psychologist, 54, 480–492.

Weiner, B. (1992). Human motivation: Metaphors, theories, and research. Newbury Park, CA: SAGE.

Weinstein, N., Przybylski, A. K., & Ryan, R. M. (2013). The integrative process: New research and future directions. Current Directions in Psychological Science, 22, 69–74.

White, J. (2010). Understanding and augmenting human morality: An introduction to the ACTWith model of conscience. In L. Magnani, W. Carnielli, and C. Pizzi (Eds.), Model-based reasoning in science & technology (pp. 607–621). Berlin: Springer.

Willingham, D. (1998). A neuropsychological theory of motor skill learning. Psychological Review, 105(3), 558–584.

Willingham, D.,Nissen, M., & Bullemer, P. (1989). On the development of procedural knowledge. Journal of Experimental Psychology: Learning, Memory, and Cognition, 15, 1047–1060. (p.427)

Wilson, N. (2012). Towards a psychologically plausible comprehensive computational theory of emotion. PhD thesis, Rensselaer Polytechnic Institute, Troy, NY.

Wilson, N., Sun, R., & Mathews, R. (2009). Performance degradation under pressure. Neural Networks, 22, 502–508.

Wilson, N., Sun, R., & Mathews, R. (2010). A motivationally based computational interpretation of social anxiety induced stereotype bias. Proceedings of the Annual Conference of the Cognitive Science Society, Portland, Oregon (pp. 1750–1755). Austin, TX: Cognitive Science Society.

Wilson, N. & Sun, R. (2014). Coping with bullying: A computational emotion-theoretic account. In P. Bello et al. (Eds.), Proceedings of the Annual Conference of Cognitive Science Society, Quebec City, Quebec, Canada (pp. 3119–3124). Austin, TX: Cognitive Science Society.

Wilson, N. & Sun, R. (in preparation). Modeling personality disorders.

Wilson, N., Sun, R., & Mathews, R. (in preparation). A detailed computational explanation of anxiety induced performance degradation.

Wine, J. (1971). Test anxiety and direction of attention. Psychological Bulletin, 76, 92–104.

Winter, D. G., John, O. P., Stewart, A. J., Klohnen, E. C., & Duncan, L. E. (1998). Traits and motives: Toward an integration of two traditions in personality research. Psychological Review, 105(2), 230–250.

Woike, B. (1995). Most memorable experiences: Evidence for a link between implicit and explicit motives and social cognitive processes in everyday life. Journal of Personality and Social Psychology, 68, 1081–1091.

Wood, W. & Quinn, J. (2005). Habits and the structure of motivation in everyday life. In J. Forgas, K. Williams, and S. Laham (Eds.), Social motivation: Conscious and unconscious processes. New York: Cambridge University Press.

Wright, I. P., & Sloman, A. (1997). MINDER1: An implementation of a proto-emotional agent architecture. Technical Report CSRP-97-1, School of Computer Science, University of Birmingham, Birmingham, UK.

Wynn, T. (2002). Archaeology and cognitive evolution. Brain and Behavioral Sciences, 25(3), 389–438.

Yerkes, R. & Dodson, J. (1908). The relation of strength of stimulus to rapidity of habit-formation. Journal of Comparative Neurology and Psychology, 18(5), 459–482.

Zajonc, R. B. (1980). Feeling and thinking: Preferences need no inferences. American Psychologist, 35(2), 151–175.

Zerubavel, E. (1997). Social mindscapes: An invitation to cognitive sociology. Cambridge, MA: Harvard University Press. (p.428)