Palabras clave
computation
computational metaphor
artificial intelligence
memoria humana
computación
metáfora computacional
inteligencia artificial
Cómo citar
Resumen
Las funciones de la memoria están íntimamente ligadas a todos los procesos cognitivos humanos. El estudio de la memoria humana está sumido en un sinnúmero de teorías y modelos de toda índole, por lo que es necesario aclarar el panorama de estudio para crear mejores aplicaciones en educación y en otras áreas relacionadas. Este artículo sobre modelos y teorías computacionales de la memoria es parte de una línea de investigación en memoria humana que busca crear un estado de la cuestión sobre el peso de los estudios actuales en el área. Se realiza una revisión crítica de 37 artículos sobre computación y memoria utilizando un instrumento de análisis que se ha denominado “tamizâ€. Se identifican los aspectos más relevantes encontrados en estos artículos y se concluye con unas observaciones generales sobre lo encontrado. Los resultados muestran que hay una gran dependencia a la utilización de la metáfora computacional de la mente para explicar los procesos cognitivos de los seres humanos.Citas
ACT-R Research Group. (s. f.). ACT-R. Recuperado de http://act-r.psy.cmu.edu/
Anderson, J. R. (1996). ACT: A simple theory of complex cognition. American Psychologist, 51, 355-365.
Anderson, J. R. y Betz, J. (2002). A hybrid model of categorization. Psychonomic Bulletin & Review, 8, 629-647.
Anderson, J. R., Bothell, D., Lebiere, C., y Matessa, M. (1998). An integrated theory of list memory. Journal of Memory and Language, 38, 341-380.
Anderson, J. R., Budiu, R. y Reder, L. M. (2001). A theory of sentence memory as part of a more general theory of memory. Journal of Memory and Language, 45, 337-367.
*Aizenbud-Reshef, N., Belinsky, E., Jacovi, M., Laufer, D. y Soroka, V. (2008). Pensieve. Augmenting human memory. CHI ‘08 extended abstracts on Human factors in computing systems, 3231-3236.
*Baddeley, A. D. (1986). Working memory. New York: Oxford University Press.
*Burgess, C. (2000). Theory and operational definitions in computational memory models: A response to Glenberg and Robertson. Journal of Memory and Language, 43, 402-408.
*Burgess, N. y Hitch, G. (2005). Computational models of working memory: putting long-term memory into context. Trends in Cognitive Sciences, 9(11), 535-541.
*Byrne, M. D. (1996) A computational theory of working memory. Conference companion on Human factors in computing systems: common ground, 31-32.
*Chartier, S., Renaud, P., y M. Boukadoum. (2008). A nonlinear dynamic artificial neural network model of memory. New Ideas in Psychology, 26, 252-277.
*Collins, A. M. (1973). Studies of human memory and language processing. (Reporte). Washington, DC: National Inst. of Education (DHEW).
*Commarford, P. M. (2006). Working memory, search, and signal detection: implications for interactive voice response system menu design. (Tesis doctoral), University of Central Florida, United States, Florida.
Dawson, J. W. (2006). Goedel and the Limits of Logic. Plus Magazine, 39. Disponible en http://plus.maths.org/issue39/features/dawson/
*Dekel, U. (2008). Designing a prothetic memory to support software developers. Companion of the 30th international conference on Software engineering, 1011-1014.
*Denhière, G. y Lemaire, B. (2004). A computational model of children’s semantic memory. In K. Forbus, D. Gentner y T. Regier (Eds.). Proceedings of the 26 th Annual Meeting of the Cognitive Science Society (pp. 297- 302), Chicago, Estados Unidos.
*Elsweiler, D. (2007). Supporting human memory in personal information management. (Tesis doctoral). Department of Computer and Information Sciences at the University of Strathclyde. Glasgow, Esocia.
*Foltz, P. W. (1991). Models of human memory and computer information retrieval: Similar approaches to similar problems (Reporte). Estados Unidos: University of Colorado, Institute of Cognitive Science.
*Hewett, T. T. (2005). Designing with the human memory in mind . Proceedings of the 7th international conference on Human computer interaction with mobile devices & services, 363-364.
Horst, S. (2005). The Computational Theory of Mind. The Stanford Encyclopedia of Philosophy, Fall 2005 Edition. Disponible en http://plato.stanford.edu/archives/fall2005/entries/computational-mind/
*Howard, M. W. (2009). Computational models of memory. In L.R. Squire (Eds.). Encyclopedia of Neuroscience, 5, (pp.771-777). Oxford: Academic Press.
*Huggett, M., Hoos, H. y Rensink, R. (2007). Cognitive principles of information management: The principles of mnemonic associative knowledge (P-MAK). Minds and Machines, 17(4), 445-485.
*Huguenard, B. R., Lerch, F. J., Junker, B. W., Patz, R. J. y Kass, R. E. (1997). Working-memory failure in phone-based interaction. ACM Transactions on Computer-Human Interaction (TOCHI), 4(2), 67-102.
*Izquierdo, E. (2008). The dynamics of learning behaviour: A situated, embodied, and dynamical systems approach. (Tesis doctoral). Universidad de Sussex. Disponible en http://eduardoizquierdo.tumblr.com/phd
*Kallinen, K., Laarni, J., Ravaja, N., y Saari, T. (2004). Gender and habitual use of media moderate the memory performance in emotional-multimodal context. Nordic Conference on Human-Computer Interaction, 82, 397-400.
*Kawamura, T., Fukuhara, T., Takeda, H., Kono, Y. y Kidode, M. (2006). Ubiquitous memories: a memory externalization system using physical objects. Personal and Ubiquitous Computing, 11(4), 287-298.
*Leake, D. B. (1994). Towards a computer model of memory search strategy learning. Proceedings of the Sixteenth Annual Conference of the Cognitive Science Society, 549-554.
*Lehman, J. F., Laird, J. y Rosenbloom, P. (2006). A gentle introduction to SOAR: 2006 update. (Reporte). Disponible en http://ai.eecs.umich.edu/soar/sitemaker/docs/misc/ GentleIntroduction-2006.pdf
*Marinier, R. P., y Laird, J. E. (2004). Toward a Comprehensive Computational Model of Emotions and Feelings. Paper presented at the Sixth International Conference on Cognitive Modeling. Pittsburgh, Pennsylvania, Estados Unidos.
McCarthy, J., Minsky, M. L., Rochester, N., y Shannon, C. E. (1955). A Proposal for the Dartmouth Summer Research Project on Artificial Intelligence. In Chrisley, R. (eds.). Artificial Intelligence: Critical Concepts, 2, (pp. 44-53). Nueva York, Estados Unidos.
McCurdock, P. (2004). Machines who think: A personal inquiry into the history and prospects of artificial intelligence (2a ed.). Massachusetts, Estados Unidos: A. K. Peters, Ltd.
*Norman, K. A, Detre, G. y Polyn, S. M. (2008). Computational models of episodic memory. In R. Sun (Ed.). The Cambridge Handbook of Computational Psycholog, (189-225). Cambridge University Press, Cambridge.
Newell, A. (1990). Unified Theories of Cognition. Cambridge, Massachusetts: Harvard University Press.
Newell y Simon (1959). The Simulation of Human Thought. Santa Mónica, California: Rand Corporation.
Nordlander, T. E. (2001). AI Surveying: Artificial Intelligence in Business. (Tesis de Maestría), Universidad de Montford, Montford, Leicester.
*O’Reilly, R. C., Braver, T. S. y Cohen, J. D. (1999). A biologically-based computational model of working memory. In A. Miyake y P. Shah (Eds.). Models of Working Memory: Mechanisms of Active Maintenance and Executive Control. (pp. 375-411), New York: Cambridge University Press.
*Rizzuto, D. S. (2002). The computational and electrophysiological foundation of item and associative memory. (Tesis doctoral). The Faculty of the Graduate School of Arts and Sciences, Brandeis University, Waltham/Boston, Massachusetts, Estados Unidos.
*Rogers, T. T. (2008). Computational models of semantic memory. In R. Sun (Ed.). The Cambridge Handbook of Computational Psychology, 226-266. New York: Cambridge University.
Russell, S., y Norvig, P. (2009). Artificial Intelligence: A Modern Approach (3ª ed.). Nueva Jersey, Estados Unidos: Prentice Hall.
*Sas, C., y Dix, A. (2006). Designing for collective remembering. Conference on Human Factors in Computing Systems, 1727-1730.
*Schoelles, M. J., Neth, H., Myers, C. W., y Gray, W. D. (2006). Steps towards integrated models of cognitive systems: A levels-of-analysis approach to comparing human performance to model predictions in a complex task environment. In Proceedings of the 28th Annual Conference of the Cognitive Science Society (pp. 756-761) . Vancouver, British Columbia, Canadá.
*Schweer, A. y Hinze, A. (2007). Challenges in interface and interaction design for context-aware augmented memory systems. Proceedings of the 7th ACM SIGCHI New Zealand chapter’s international conference on Computer-human interaction: design centered HCI, 55-58.
Searle, J. R. (1980). Minds, Brains, and Programs. The Behavioral and Brain Sciences, 3, 417-457.
*Shastri, L. (2001). A computational model of episodic memory formation in the hippocampal system. Neurocomputing, Volúmenes 38-40: 889-897.
*Steyvers, S., Griffiths, T. L., y Dennis, S. (2006). Probabilistic inference in human semantic memory. TRENDS in Cognitive Sciences, 10(7).
*Sun, R. (2004). The CLARION Cognitive Architecture: Extending Cognitive Modeling to Social Simulation. In Sun, R. (eds). Cognition and Multi-Agent Interaction, (pp. 79-103). Nueva York, Estados Unidos: Cambridge University Press.
Sun, R. (2009). Theoretical status of computational cognitive modeling. Cognitive Systems Research, 10(2), 124-140.
Turing, A. (1950). Computing Machinery and Intelligence. Mind, 49, 433-460.
Van den Hoben, E., Eggen, B. (2007). Informing augmented memory system design through autobiographical memory theory. Personal and Ubiquitous Computing, 12(6), 433-443.
Van Gelder, T. (1998). The Dynamical Hypothesis in Cognitive Science. The Behavior and Brain Sciences, 21, 615-665.
Vemuri, S., Schmandt, C. y Bender, W. (2006). ¡Remember: A personal, long-term memory prosthesis. Proceedings of the 3rd ACM workshop on Continuous archival and retrival of personal experences, 65-74.
Von Eckardt, B. (1993). What is cognitive science? Cambridge, Massachusetts: The MIT Press.
West, D., Quigley, A. y Kay, J. (2007). MEMENTO: a digital-physical scrapbook for memory sharing. Personal and Ubiquitous Computing, 11(4), 313-328.