Matthew Klenk

Qualitative Reasoning Group
Cognitive Systems Division
Department of Electrical Engineering and Computer Science
Northwestern University
m-klenk at northwestern.edu


Education

B.A. Computer Science, Emory University, May 2003
M.S. Computer Science, Northwestern University, December 2006
Ph.D. Computer Science, Northwestern University, expected December 2008

Research Interests

Analogical Reasoning and Learning

Analogy has long been seen as a method for knowledge based systems to overcome brittleness. But there are still many open questions concerning exactly when and how analogy can be employed to overcome this issue.

 

·         Using within domain analogical model formulation to overcome brittleness in knowledge-base systems

·         Using cross domain analogy to accelerate learning of all knowledge structures in new domains

Intelligent Architecture Development

When we begin to think of AI systems that exist over time operating over a range of tasks requiring intelligence, a number of important research areas arise. I have begun to addressing some of these while working on the Companions cognitive systems project.

 

·         Exploring broader and more complex tasks with which to evaluate intelligent architectures

·         Using multi-modal interaction to increase the communication bandwidth with users and reason over diverse representations

 

Publications

Selected Conferences and Journals

 

1.       Klenk, M. and Forbus, K. (under review). Domain Transfer via Cross-Domain Analogy. Cognitive Systems Research, Special Issue on “Analogies: Integrating Cognitive Abilities”. Elsevier.

2.       Klenk, M., Forbus, K., Tomai, E., and Kim, H. (under review). Using Analogical Model Formulation with Sketches to Solve Bennett Mechanical Comprehension Test Problems. Journal Experimental and Theoretical Artificial Intelligence, Special Issue on “Test-Based AI”. Taylor & Francis.

3.       Dehghani, M., Tomai, E., Forbus, K., and Klenk, M. 2008. An Integrated Reasoning Approach to Moral Decision-Making. Proceedings of AAAI-08: 23rd National Conference on Artificial Intelligence. Chicago, IL. 24% acceptance rate. [pdf]

4.       Klenk, M. and Forbus, K. 2007. Measuring the level of transfer learning by an AP Physics problem-solver. Proceedings of AAAI-07: 22nd National Conference on Artificial Intelligence, Vancouver, BC. 27% acceptance rate. [pdf]

5.       Klenk, M., Forbus, K., Tomai, E., Kim,H., and Kyckelhahn, B. 2005. Solving Everyday Physical Reasoning Problems by Analogy using Sketches. Proceedings of AAAI-05: 20th National Conference on Artificial Intelligence, Pittsburgh, USA. 18% acceptance rate. [pdf]

Conferences

 

1.       Dehghani, M., Tomai, E., Forbus, K., Iliev, R., and Klenk, M. 2008. MoralDM: A Computational Modal of Moral Decision-Making. Proceedings of the 30th Annual Conference of the Cognitive Science Society (CogSci), Washington, D.C. [pdf]

2.       Klenk, M. and Forbus, K. 2007. Cognitive modeling of analogy events in physics problem solving from examples. Proceedings of the 29th Annual Conference of the Cognitive Science Society (CogSci). Nashville, TN. [pdf]

3.       Paritosh, P.K. and Klenk, M. 2006. Cognitive Processes in Quantitative Estimation: Analogical Anchors and Causal Adjustment. Proceedings of the 28th Annual Conference of the Cognitive Science Society (CogSci). Vancouver, BC. [pdf]

Workshops and Symposia

 

1.       Forbus, K., HInrichs, T., and Klenk, M., 2008. Companion Cognitive Systems: Design Goals and Some Lessons Learned. AAAI Fall Symposium on Naturally-Inspired Artificial Intelligence, Washington, DC, USA. [pdf]

2.       Klenk, M., Friedman, S., and Forbus, K. 2008. Learning Modeling Abstractions via Generalization. 22nd International Workshop on Qualitative Reasoning. Boulder, CO. [pdf]

3.       Dehghani, M., Tomai, E., Forbus, K., and Klenk, M. 2008. Order of Magnitude Reasoning in Modeling Moral Decision-Making. 22nd International Workshop on Qualitative Reasoning. Boulder, CO. [pdf]

4.       Klenk, M. and Forbus, K. 2007. Cross domain analogies for learning domain theories. In Angela Schwering et al. (Eds.), Analogies: Integrating Multiple Cognitive Abilities. Publications of the Institute of Cognitive Science, University of Osnabrück, Volume 5-2007 [pdf]

5.       Klenk, M. and Forbus, K. 2007. Learning domain theories via analogical transfer. Proceedings of 21st International Workshop on Qualitative Reasoning. Aberystwyth, U.K. [pdf]

6.       Klenk, M. and Forbus, K. 2006. Analogical Model Formulation for AP Physics Problems. 20th International Workshop on Qualitative Reasoning. Hanover, USA. [pdf]

7.       Klenk, M., Forbus, K., Tomai, E., Kim,H., and Kyckelhahn, B. 2005. Solving Everyday Physical Reasoning Problems by Analogy using Sketches. Proceedings of 19th International Workshop on Qualitative Reasoning. Graz, Austria. [pdf]

8.       Forbus, K., Lockwood, K., Klenk, M., Tomai, E., and Usher, J. 2004. Open-domain sketch understanding: The nuSketch approach. AAAI Fall Symposium on Making Pen-based Interaction Intelligent and Natural, Washington, DC, USA. [pdf]

Awards

·         2004-2005 Piros Fellowship

·         2007-2008 Walter P. Murphy Chair Fellowship