I am currently a faculty member in the Computer Science Department at Sarah Lawrence College in Bronxville, New York. I received my Ph.D. in Computer Science and Cognitive Science from Indiana University under the direction of Douglas Hofstadter. While at IU, I was a member of the Center for Research on Concepts and Cognition, the Department of Computer Science, and the Cognitive Science Program. Before coming to Sarah Lawrence, I taught for several years at Swarthmore and Pomona.
O'Hara, K., Blank, D., and Marshall, J. (2015). Computational notebooks for AI education. Proceedings of the 28th International FLAIRS Conference, pp. 263-268. Palo Alto, CA: AAAI Press. Nominated for Best Paper award.
Georgeon, O. and Marshall, J. (2013). Demonstrating sensemaking emergence in artificial agents: a method and an example. International Journal of Machine Consciousness, 5(2), pp. 131-144. DOI: 10.1142/S1793843013500029.
Georgeon, O., Marshall, J., and Manzotti, R. (2013). ECA: an enactivist cognitive architecture based on sensorimotor modeling. Biologically Inspired Cognitive Architectures, 6, pp. 46-57. DOI: 10.1016/j.bica.2013.05.006.
Blank, D., Kay, J., Marshall, J., O'Hara, K., and Russo, M. (2012). Calico: a multi-programming-language, multi-context framework designed for computer science education. Proceedings of the 43rd ACM Technical Symposium on Computer Science Education, SIGCSE '12, pp. 63-68. New York: ACM.
Georgeon, O., Marshall, J., and Gay, S. (2012). Interactional motivation in artificial systems: between extrinsic and intrinsic motivation. Proceedings of the Joint IEEE Conference on Development and Learning and Epigenetic Robotics (ICDL-Epirob 2012), San Diego, pp. 1-2.
Georgeon, O. and Marshall, J. (2012). The small loop problem: a challenge for artificial emergent cognition. Proceedings of the International Conference on Biologically Inspired Cognitive Architectures (BICA 2012), Palermo, Italy, pp. 137-144.
Georgeon, O., Marshall, J., and Ronot, P.-Y. (2011). Early-stage vision of composite scenes for spatial learning and navigation. Proceedings of the Joint IEEE Conference on Development and Learning and Epigenetic Robotics (ICDL-Epirob 2011), Frankfurt, Germany, pp. 224-229.
Lee, R., Walker, R., Meeden, L., and Marshall, J. (2009). Category-based intrinsic motivation. In L. Canamero, P.-Y. Oudeyer, & C. Balkenius (eds.), Proceedings of the Ninth International Conference on Epigenetic Robotics: Modeling Cognitive Development in Robotic Systems, pp. 81-88. Lund University Cognitive Studies, 146. Lund: LUCS.
Marshall, J. (2008). Leveraging the Singularity: introducing AI to liberal arts students. Proceedings of the 2008 AAAI Workshop on Artificial Intelligence Education, pp. 62-67. Menlo Park, CA: AAAI Press.
Marshall, J., Makhija, N., and Rothman, Z. (2008). The introspective robot: using self-prediction to improve robot learning. Proceedings of the 21st International FLAIRS Conference, pp. 117-118. Menlo Park, CA: AAAI Press.
Blank, D., Kumar, D., Marshall, J., and Meeden, L. (2007). Advanced robotics projects for undergraduate students. AAAI 2007 Spring Symposium: Robots and Robot Venues: Resources for AI Education, pp. 10-15. Menlo Park, CA: AAAI Press.
Blank, D., Marshall, J., and Meeden, L. (2007). What is it like to be a developmental robot? AMD Newsletter: The Newsletter of the Autonomous Mental Development Technical Committee, vol. 4, no. 1, pp. 7-8.
Marshall, J. (2006). A self-watching model of analogy-making and perception. Journal of Experimental and Theoretical Artificial Intelligence, 18(3), pp. 267-307.
Blank, D., Lewis, J., and Marshall, J. (2005). The multiple roles of anticipation in developmental robotics. AAAI 2005 Fall Symposium: From Reactive to Anticipatory Cognitive Embodied Systems, pp. 8-14. Menlo Park, CA: AAAI Press.
Blank, D., Kumar, D., Meeden, L., and Marshall, J. (2005). Bringing up robot: fundamental mechanisms for creating a self-motivated, self-organizing architecture. Cybernetics and Systems, 36(2), pp. 125-150.
Marshall, J., Blank, D., and Meeden, L. (2004). An emergent framework for self-motivation in developmental robotics. In J. Triesch & T. Jebara (eds.), Proceedings of the 3rd International Conference on Development and Learning (ICDL 2004), pp. 104-111. La Jolla, CA: UCSD Institute for Neural Computation.
Marshall, J. (2004). An introductory CS course for cognitive science students. AAAI 2004 Spring Symposium: Accessible Hands-on Artificial Intelligence and Robotics Education, pp. 97-101. Menlo Park, CA: AAAI Press.
Marshall, J. (2002). Metacat: a self-watching cognitive architecture for analogy-making. In W. D. Gray & C. D. Schunn (eds.), Proceedings of the 24th Annual Conference of the Cognitive Science Society, pp. 631-636. Mahwah, NJ: Lawrence Erlbaum Associates.
Marshall, J. (2002). Metacat: a program that judges creative analogies in a microworld. In C. Bento, A. Cardoso, & G. A. Wiggins (eds.), Proceedings of the 2nd Workshop on Creative Systems: Approaches to Creativity in Artificial Intelligence and Cognitive Science, pp. 77-84, 15th European Conference on Artificial Intelligence (ECAI 2002), Lyon, France.
Metacat: A Self-Watching Cognitive Architecture for Analogy-Making and High-Level Perception. Ph.D. dissertation, Indiana University, Bloomington, 1999.
Marshall, J. and Hofstadter, D. (1998). Making sense of analogies in Metacat. In K. Holyoak, D. Gentner, and B. Kokinov (eds.), Advances in Analogy Research: Integration of Theory and Data from the Cognitive, Computational, and Neural Sciences, pp. 118-123. Sofia: New Bulgarian University.
Marshall, J. and Hofstadter, D. (1997). The Metacat project: a self-watching model of analogy-making. Cognitive Studies: Bulletin of the Japanese Cognitive Science Society, 4(4), 57-71. Reprinted in Japanese translation in A. Ohnishi & H. Suzuki (eds.), Similarity-Based Approach to Mind, pp. 202-222. Tokyo: Kyoritsu Shuppan, 2001.
Marshall, J. (1997). From Copycat to Metacat: developing a self-watching framework for analogy-making. In T. Veale (ed.), Proceedings of Mind II: Computational Models of Creative Cognition, Dublin City University, Ireland.
Marshall, J. and Hofstadter, D. (1996). Beyond Copycat: incorporating self-watching into a computer model of high-level perception and analogy-making. In M. Gasser (ed.), Online Proceedings of the 1996 Midwest Artificial Intelligence and Cognitive Science Conference, Indiana University, Bloomington. [PDF]
Blank, D., Meeden, L., and Marshall, J. (1992). Exploring the symbolic/subsymbolic continuum: a case study of RAAM. In J. Dinsmore (ed.), The Symbolic and Connectionist Paradigms: Closing the Gap, pp. 113-148. Hillsdale, NJ: Lawrence Erlbaum Associates.
Contact InformationJim Marshall
Computer Science Department
Sarah Lawrence College
One Mead Way
Bronxville, NY 10708 USA
Phone/voicemail: (914) 395-2673
Fax: (914) 395-2662
Email: j + (my last name) + @slc.edu
Springtime at Sarah Lawrence