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.

• Click here for a picture of me in my younger days.

• Introduction to Computer Science: The Way of the Program
  • Lectures: Tuesday and Thursday 3:05 - 4:30 pm, Titsworth Lecture Hall
  • Lab 1: Wednesday 11:00 am - 12:25 pm, Science 104
  • Lab 2: Wednesday 3:05 - 4:30 pm, Science 104
  • Group conference 1: Friday 10:00 - 10:55 am, Science 301
  • Group conference 2: Friday 12:30 - 1:25 pm, Science 301
  
  
• Principles of Programming Languages
  • Tuesday and Thursday 9:25 - 10:50 am, Science 104

• Data Structures and Algorithms
• Artificial Intelligence and Society
• Intermediate Programming in Python
• Bio-Inspired Artificial Intelligence
• Quantum Computing
• FYS: Achilles, the Tortoise, and the Mystery of the Undecidable
• Introduction to Functional Programming
• The Computational Beauty of Nature
• Is the Singularity Near?
• Artificial Minds
• Hello World: An Overview of Computer Science
• Computer Science: An Accelerated Introduction (Java)
• Computation and Cognition

• CS 30 Computation and Cognition (Python)
• CS 30 Computation and Cognition (Scheme)
• CS 50 Introduction to Computer Science
• CS 131 Programming Languages
• CS 151 Artificial Intelligence
• CS 152 Neural Networks
• CS 190 Senior Seminar (Fall 2005)
• CS 190 Senior Seminar (Fall 2004)

• CS 21 The Imperative Paradigm: UNIX and C
• CS 22 Structure and Interpretation of Computer Programs
• CS 35 Algorithms and Object-Oriented Programming
• CS 43 Principles of Programming Languages
• CS 97 Senior Conference: Evolutionary Computation

• Blank, D. and Marshall, J. (2023). The Calysto Scheme project. ICFP 2023 Workshop on Scheme and Functional Programming, Seattle, WA. arXiv:2310.10886

• Blank, D., Marshall, J., and Meeden, L. (2017). A developmental robotics manifesto. IEEE CIS Newsletter on Cognitive and Developmental Systems, vol. 14, no. 1, pp. 6-7.

• Meeden, L., Blank, D., and Marshall, J. (2017). Curiosity: emergent behavior through interacting multi-level predictions. Position paper and poster presented at the Designing for Curiosity Workshop, ACM Conference on Human Factors in Computing Systems (CHI 2017), Denver.

• Marshall, J. (2016). Model AI Assignments: A Genetic Algorithm for Robby the Robot, and A Simple Genetic Algorithm. Proceedings of the Sixth Symposium on Educational Advances in Artificial Intelligence (EAAI-2016), pp. 4139-40. Palo Alto, CA: AAAI Press.

• Wollowski, M., Selkowitz, R., Brown, L., Goel, A., Luger, G., Marshall, J., Neel, A., Neller, T., and Norvig, P. (2016). A survey of current practice and teaching of AI. Proceedings of the Sixth Symposium on Educational Advances in Artificial Intelligence (EAAI-2016), pp. 4119-24. Palo Alto, CA: AAAI Press.

• 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.

• Dindo, H., Marshall, J., and Pezzulo, G. (2013). Editorial: conceptual commitments of AGI systems. Journal of Artificial General Intelligence, 4(2), pp. 23-25. DOI: 10.2478/jagi-2013-0004.

• 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 Home Page

• 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.

• 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 Information Jim Marshall Computer Science Department Sarah Lawrence College One Mead Way Bronxville, NY 10708 USA Office: Alice Ilchman Science Center 100 Phone/voicemail: (914) 395-2673 Fax: (914) 395-2662 Email: j + (my last name) + @sarahlawrence.edu

Springtime at Sarah Lawrence