Lisa Meeden

AI Toolkit (aitk)

Research

• Vita
• Papers

Past Courses

Grants

Neil R. Grabois Professor in Natural Sciences and Engineering
Computer Science Department
Swarthmore College
500 College Ave.
Swarthmore, PA 19081
610-328-8565
meeden@cs.swarthmore.edu

I am a Full Professor in the Computer Science Department at Swarthmore College. I also participate in the interdisciplinary program Cognitive Science. I received my Ph.D. in Computer Science with a minor in Cognitive Science from Indiana University. I received my B.A. in Mathematics from Grinnell College.

Fall 2024

On sabbatical

Artificial Intelligence Toolkit (aitk)

Developed in collaboration with Doug Blank and James Marshall and first released in 2021, this toolkit contains both an open source set of Python tools and a set of computational essays for exploring and understanding Artificial Intelligence, Cognitive Science, Machine Learning, and Robotics. The code and essays are designed to work easily in any web browser and allow users to gain valuable hands-on experience with these important topics. The essays were significantly expanded in Summer 2024 with the help of three Swarthmore College undergraduates Levin Ho, Morgan McErlean, and Alex You. The toolkit is available at github.com/ArtificialIntelligenceToolkit/aitk.

Selected Papers

• AI Toolkit: Libraries and Essays for Exploring the Technology and Ethics of AI co-authored with Levin Ho, Morgan McErlean, Zehua You, and Douglas Blank, Proceedings of the Conference on Educational Advances in AI, in Philadelphia, PA, March 2025.
• Experimental Evidence that Empowerment May Drive Exploration in Sparse-Reward Environments co-authored with Francesco Massari, Martin Biehl, and Ryota Kanai, Proceedings of the IEEE International Conference on Development and Learning, in Bejing, China, August 2021.
• Developing Grounded Goals through Instant Replay Learning co-authored with Douglas Blank, Seventh Joint IEEE International Conference on Development and Learning and on Epigenetic Robotics in Lisbon, Portugal, September 2017.
• A Developmental Robotics Manifesto co-authored with Douglas Blank and James Marshall, IEEE CIS Newsletter on Cognitive and Developmental Systems, Volume 14, Spring 2017.
• Curiosity: Emergent behavior through interacting multi-level predictions and poster co-authored with Douglas Blank and James Marshall. Presented at the Workshop Designing for Curiosity held in conjunction with the Conference Computer Human Interaction in Denver, CO, May 2017.
• Book Review of Angelo Cangelosi and Matthew Schlesinger: Developmental Robotics in Genetic Programming and Evolvable Machines, Volume 16, Issue 3, 2015.
• A support program for introductory CS courses that improves student performance and retains students from underrepresented groups, co-authored with Tia Newhall, Andy Danner, Ameet Soni, Frances Ruiz, and Richard Wicentowski. Proceedings of Special Interest Group in Computer Science Education, 2014.
• Category-Based Intrinsic Motivation, co-authored with Rachel Lee, Ryan Walker, and James Marshall. Proceedings of the Ninth International Conference on Epigenetic Robotics, 2009.
• Editorial: Introduction to Developmental Robotics, co-authored with Douglas Blank. Connection Science, Volume 18, Number 2, 2006.
• Bringing up robot: Fundamental mechanisms for creating a self-motivating, self-organizing architecture, co-authored with Douglas Blank, Deepak Kumar, and James Marshall. Cybernetics and Systems, Volume 36, Number 2, 2005.
• An emergent framework for self-motivation in developmental robotics, co-authored with James Marshall and Douglas Blank, presented at The Third International Conference on Development and Learning, 2004.
• Heterogeneity in the coevolved behaviors of mobile robots: The emergence of specialists, co-authored with Mitchell Potter and Alan Schultz, Proceedings of the Seventeenth International Joint Conference on Artificial Intelligence, Morgan Kaufmann, 2001.
• REAPER: A Reflexive Architecture for Perceptive Agents, co-authored with Bruce Maxwell, Nii Saka Addo, Paul Dickson, Nathaniel Fairfield, Nik Johnson, Edward Jones, Suor Kim, Pukar Malla, Matthew Murphy, Brandon Rutter, and Eli Silk, AI Magazine, volume 22, number 1, 2001.
• Nature versus Nurture in Evolutionary Computation: Balancing the Roles of the Training Environment and the Fitness Function in Producing Behavior, co-authored with Jordan Wales and Jesse Wells, GECCO Late Breaking Paper, 2000.
• Integrating Robotics Research with Undergraduate Education, co-authored with Bruce Maxwell, Special Issue of IEEE Intelligent Systems, edited by Robin Murphy, volume 15, number 6, 2000.
• Trends in Evolutionary Robotics, co-authored with Deepak Kumar, Soft Computing for Intelligent Robotic Systems, edited by L.C. Jain and T. Fukuda, Physica-Verlag, New York, NY, pages 215-233, 1998.
• Bridging the gap between robot simulations and reality with improved models of sensor noise, Proceedings of the Third Annual Conference on Genetic Programming, edited by Koza, J.R, et. al., Morgan Kaufmann Publishers, San Francisco, CA, pages 824-831, 1998.
• A Hybrid Connectionist and BDI Architecture for Modeling Embedded Rational Agents, co-authored with Deepak Kumar, presented at the Workshop on Cognitive Robotics, AAAI Fall Symposium Series at MIT, October, 1998.
• Learning in autonomous robots: A summary of the 1996 Robolearn Workshop, co-authored with Henry Hexmoor, Knowledge Engineering Review, Volume 11, Issue 4, 1997.
• An incremental approach to developing intelligent neural network controllers for robots, IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, Volume 26, Number 3, pages 474-485, 1996.
• Towards planning: Incremental investigations into adaptive robot control, unpublished dissertation done under the guidance of Mike Gasser at Indiana University, 1994.
• Emergent control and planning in an autonomous vehicle, co-authored with Gary McGraw and Doug Blank, Proceedings of the Fifteenth Annual Conference of the Cognitive Science Society, Lawrence Erlbaum Associates, Hillsdale, NJ, pages 735-740, 1993.
• Exploring the symbolic/subsymbolic continuum: A case study of RAAM, co-authored with Doug Blank and James Marshall, The Symbolic and Connectionist Paradigms: Closing the Gap, edited by J. Dinsmore, Lawrence Erlbaum Associates, Hillsdale, NJ, pages 113-148, 1992.

Past courses

• Mini course on AI for faculty and staff (Summer 2024), sponsored by Swarthmore College's Teaching and Learning Commons.
• Summer Scholars Program (2023, 2018)
• CS19/PHIL27 Ethics and Technology (S24)
• CS21 Introduction to Computer Science (F20, S20, S18, S16, F14, F10, S08)
• CS21B Intro to CS: Applications in Biology (S11, S10)
• CS35 Data Structures and Algorithms (F23, S23, F21, F18, S18[lab], F09)
• CS37 The Structure and Interpretation of Computer Programs (S06)
• CS63 Artificial Intelligence (S24[lab], F22, S22, F19, S19, S16, S15, F13, F11, F07, F05)
• CS75 Compiler Construction (S11, S07)
• CS81 Adaptive Robotics (F17, F15, S14, S12, S10, S09, S08, S06, S03)
• COGS1 Introduction to Cognitive Science (S07)

Grants

• National Humanities Center Grant (2022-2024), Responsible Artificial Intelligence Curriculum Design Project. Working in conjunction with Krista Thomason in Philosophy to develop a new team-taught course covering the ethics and practice of AI.
• NSF CCLI EMD grant (2003-2006) Beyond LEGOs: Hardware, Software, and Curriculum for the Next Generation Robot Laboratory
• The Pyro software developed with the support of the grant
• Pyro received the NEEDS 2005 Premier Award for Excellence in Engineering Education Courseware
• See publications resulting from the grant
• NSF ILI grant (1996-1998) A robot-based laboratory for teaching Artificial Intelligence
  • Developed as a result of the grant, Resource kit: A robot laboratory for teaching AI