Lazerman, Lexx L. (2012) A Theoretical Cognitive Construct of a 3D Embodied Agent: VAL, the Virtual Autonomous Learner. Masters thesis, Concordia University.
|PDF (Thesis) - Accepted Version|
The cognitive sciences have always educated educators by providing a pedagogical framework as a guide. However, the standard cognitive sciences are being challenged by a new paradigm, embodied cognition, in which learning is part of a dynamical system. In this paradigm, virtual embodiment (VE) is the new artificial intelligence (AI). This thesis is an application of VE, introducing an approach to developing a virtual 3D agent that has the potential to achieve “strong AI” status. I believe such agents can mature into AI educators. And that the development of a great AI educator starts with the development of a humble AI child. My methodological approach is a metasynthesis of a broad range of disciplines and consists of (1) the use of empirical research to ground my ideas, (2) the integration of dissimilar research to construct new ideas, and (3) the use of thought experiments to uncover the fundamental nature of learning within an embodiment paradigm. As a result, this thesis introduces a virtual 3D agent, the virtual autonomous learner (VAL), along with key elements of its ecological construct. With an embodied cognitive perspective, VAL seeks to find its own affordance and that of its environment. I conclude that (1) the construct for VAL needs to accommodate different cognitive architectures if we are to make full use of its methodology; (2) a rigorous virtual curriculum must be developed, and efficient pedagogical tools should be designed and developed to implement this curriculum; and (3) an educational perspective is paramount for this project.
|Divisions:||Concordia University > Faculty of Arts and Science > Education|
|Item Type:||Thesis (Masters)|
|Authors:||Lazerman, Lexx L.|
|Date:||30 March 2012|
|Thesis Supervisor(s):||Dr. Venkatesh, Vivek|
|Keywords:||cognitive science, embodied cognition, dynamical system, virtual embodiment (VE), artificial intelligence (AI), strong AI, virtual autonomous learner (VAL), virtual 3D agent, affordance, thought experiments, virtual curriculum|
|Deposited By:||LEXX L. LAZERMAN|
|Deposited On:||19 Jun 2012 14:41|
|Last Modified:||19 Jun 2012 14:41|
Allen, P., & Greaves, M. (2011). The singularity isn't near. Message posted to http://www.technologyreview.com/blog/guest/27206/
Alpaydin, E. (2004). Introduction to machine learning. Cambridge, MA: MIT Press.
Beck, J., Stern, M., & Haugsjaa, E. (1996). Applications of AI in education. Crossroads, 3(1), 11–15.
Best, B. J., & Lebiere, C. (2006). Cognitive agents interacting in real and virtual worlds. In R. Sun (Ed.), Cognition and multi-agent interaction: From cognitive modeling to social simulation (pp. 186–218). New York, NY: Cambridge University Press.
Birkholz, P. (2010). About articulatory speech synthesis. VocalTractLab. Retrieved from http://www.vocaltractlab.de/index.php?page=background-articulatory-synthesis
Boeing, A., & Bräunl, T. (2007). Evaluation of real-time physics simulation systems. Proceedings of the 5th International Conference on Computer Graphics and Interactive Techniques in Australia and Southeast Asia (pp. 281–288). Perth, Australia.
Boulos, M. N. K., Hetherington, L., & Wheeler, S. (2007). Second life: An overview of the potential of 3-D virtual worlds in medical and health education. Health Information & Libraries Journal, 24(4), 233–245.
Brooks, R. A. (1991). Intelligence without reason. Proceedings of the International Joint Conference on Artificial Intelligence (pp. 569–597). Sydney, Australia.
Brooks, R. A., Breazeal, C., Marjanovic, M., Scassellati, B., & Williamson, M. M. (1999). The Cog project: Building a humanoid robot. In C. L. Nehaniv (Ed.), Computation for metaphors, analogy, and agents (pp. 52–87). New York, NY: Springer-Verlag.
Chen, Q., & Verguts, T. (2010). Beyond the mental number line: A neural network model of number–space interactions. Cognitive Psychology, 60(3), 218–240.
Clark, A. (1999). An embodied cognitive science? Trends in Cognitive Sciences, 3(9), 345–351.
Cotterill, R. (2003). CyberChild: A simulation test-bed for consciousness studies. Journal of Consciousness Studies, 10(4-5), 31–45.
Gamez, D. (2008). Progress in machine consciousness. Consciousness and Cognition, 17(3), 887–910.
Edelman, G. M., & Mountcastle, V. B. (1978). The mindful brain: Cortical organization and the group–selective theory of higher brain function. Cambridge, MA: MIT Press.
Ferrée, T. C., & Lockery, S. R. (1999). Computational rules for chemotaxis in the nematode C. elegans. Journal of Computational Neuroscience, 6(3), 263–277.
Gallagher, S. (2005). How the body shapes the mind. Oxford, England: Clarendon.
Gamez, D. (2008). Progress in machine consciousness. Consciousness and Cognition, 17(3), 887–910.
Gibson, J. J. (1979). The ecological approach to visual perception. Boston, MA: Houghton Mifflin.
Gladwell, M. (2005). Blink: The power of thinking without thinking. New York, NY: Little Brown.
Goertzel, B., & Pennachin, C. (Eds.). (2007). Artificial general intelligence. New York, NY: Springer.
Good, T. L. (1981). Teacher expectations and student perceptions: A decade of research. Educational Leadership, 38(5), 415–422.
Google (2012, February 1). Company. Retrieved from http://www.google.com/about/company/
Gopnik, A. (2009). The philosophical baby: What children's minds tell us about truth, love & the meaning of life. London, England: Bodley Head.
Gopnik, A. (2011). What do babies think? TEDGlobal 2011, Filmed July 2011, Posted October 2011, retrieved from http://www.ted.com/talks/alison_gopnik_what_do_babies_think.html
Greenspan, S. I., & Shanker, S. (2004). The first idea: How symbols, language, and intelligence evolved from our primate ancestors to modern humans. Cambridge, MA: Da Capo Press.
Hawkins, J., & Blakeslee, S. (Eds.). (2004). On intelligence. New York, NY: Times Books.
Hayward, V., Astley, O., Cruz-Hernandez, M., Grant, D., & Robles-De-La-Torre, G. (2004). Haptic interfaces and devices. Sensor Review, 24(1), 16–29.
Jaynes, J. (1990). The origin of consciousness in the breakdown of the bicameral mind. Boston, MA: Houghton Mifflin.
Keller, H., Yovsi, R., Borke, J., Kartner, J., Jensen, H., & Papaligoura, Z. (2004). Developmental consequences of early parenting experiences: Self-recognition and self-regulation in three cultural communities. Child Development, 75(6), 1745–1760.
Kitano, H., Hamahashi, S., & Luke, S. (1998). The perfect C. elegans project: An initial report. Artificial Life, 4(2), 141–156.
Kurzweil, R. (1999). The age of spiritual machines: When computers exceed human intelligence. New York: Viking.
Kurzweil, R. (2005). The singularity is near: When humans transcend biology. New York, NY: Penguin.
Lockery, S. R. (2011). The computational worm: Spatial orientation and its neuronal basis in C. elegans. Current Opinion in Neurobiology, 21(5), 782–790.
Lorenz, B., & Barnard, E. (2007). A brief overview of artificial intelligence focusing on computational models of emotions. 2007 5th IEEE International Conference on Industrial Informatics (pp. 76–123). Vienna, Austria: IEEE.
Lowensohn, J. (2010, November 30). Kinect's open-source ambitions. CNet: News, 149. Retrieved from http://news.cnet.com/8301-10805_3-20023614-75.html
Marr, D. (1982). Vision: A computational investigation into the human representation and processing of visual information. San Francisco, CA: W. H. Freeman.
Metta, G. (2010). The iCub humanoid robot: An open-systems platform for research in cognitive development. Neural Networks, 23(8-9), 1125–1134.
McCarthy, J. (2008). The well-designed child. Artificial Intelligence, 172(18), 2003–2014.
Montague, R. (2006). Why choose this book? How we make decisions. New York, NY: Dutton.
Mountcastle, V. B. (1997). The columnar organization of the neocortex. Brain, 120(4), 701–722.
Mueller, S. T., & Minnery, B. S. (2008). Adapting the Turing test for embodied neurocognitive evaluation of biologically-inspired cognitive agents. Proceedings from the 2008 AAAI Fall Symposium on Biologically Inspired Cognitive Architectures (pp. 117–126).
Needham, A., Barrett, T., & Peterman, K. (2002). A pick-me-up for infants’ exploratory skills: Early simulated experiences reaching for objects using ‘sticky mittens’ enhances young infants’ object exploration skills. Infant Behavior and Development, 25(3), 279–295.
O'Reilly, R. C., & Munakata, Y. (2000). Computational explorations in cognitive neuroscience: Understanding the mind by simulating the brain. Cambridge, MA: MIT Press.
Penfield, W. (1961). Activation of the record of human experience. Annals of the Royal College of Surgeons of England, 29(2), 77–84.
Pfeifer, R., Bongard, J., & Grand, S. (2007). How the body shapes the way we think: A new view of intelligence. Cambridge, MA: MIT Press.
Piaget, J. (1977). In H. E. Gruker & J. Vonèche (Eds.), The Essential Piaget. London, England: Routledge & Kegan Paul.
Rickel, J., & Johnson, W. L. (2000). Task-oriented collaboration with embodied agents in virtual worlds. In J. Cassell, J. Sullivan, S. Prevost, & E. F. Churchill (Eds.), Embodied conversational agents (pp. 95–122). Cambridge, MA: MIT Press.
Ridley, M. (2003). Nature via nurture: Genes, experience, and what makes us human. New York, NY: HarperCollins.
Rittenhouse, C. D., Shouval, H. Z., Paradiso, M. A., & Bear, M. F. (1999). Monocular deprivation induces homosynaptic long-term depression in visual cortex. Nature, 397(6717), 347–350.
Rogers, B., & Arvedson, J. (2005). Assessment of infant oral sensorimotor and swallowing function. Mental Retardation and Developmental Disabilities Research Reviews, 11(1), 74–82.
Rucinski, M., Cangelosi, A., & Belpaeme, T. (2011). An embodied developmental robotic model of interactions between numbers and space. Annual Conference of the Cognitive Science Society (pp. 237–242). Austin, TX: Cognitive Science Society.
Searle, J. R. (1980). Minds, brains, and programs. Behavioral and Brain Sciences, 3(3), 417–424.
Shapiro, L. (2011). Embodied cognition. New York, NY: Routledge.
Shultz, T. R. (2003). Computational developmental psychology. Cambridge, MA: MIT Press.
Sims, K., (1994). Evolving virtual creatures. Computer Graphics (Siggraph '94 Proceedings), 15–22.
Smith, L. B., & Thelen, E. (2003). Development as a dynamic system. Trends in Cognitive Sciences, 7(8), 343–348.
Stavness, I., Lloyd, J. E., Payan, Y., & Fels, S. (2011). Coupled hard-soft tissue simulation with contact and constraints applied to jaw-tongue-hyoid dynamics. International Journal for Numerical Methods in Biomedical Engineering, 27(3), 367–390.
Streeter, T. (2003). Autonomous virtual humans. Tyler Steeter website. Retrieved from http://www.tylerstreeter.net/#AutonomousVirtualHumans
Sun, R. (2007). The importance of cognitive architectures: An analysis based on CLARION. Journal of Experimental & Theoretical Artificial Intelligence, 19(2), 159–193. doi:10.1080/09528130701191560
Turing, A. M. (1950). Computing machinery and intelligence. Mind, 59(236), 433–460.
Wilson, M. (2002). Six views of embodied cognition. Psychonomic Bulletin and Review, 9(4), 625–636.
Winchester, S. J. (1985). Locke and the innatists. History of Philosophy Quarterly, 2(4), 411–420.
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