Qualitative Reasoning Group

Northwestern University

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Papers

This is a partial collection of our group's research papers. Please send us email to get papers or reprints that are not available for downloading here.

See papers listed by year.

Quick links:

Papers on Analogy and Similarity
Papers on Companion Cognitive Systems
Papers on Conceptual Learning
Papers on Educational Software
Papers on Intelligence Analysis
Papers on Interactive Entertainment
Papers on Learning by Reading
Papers on Natural Language Semantics
Papers on Ontology and Granular Partitions
Position Papers and Commentaries
Papers on Qualitative Reasoning:
Common Sense Reasoning, Compositional Modeling, Engineering Problem Solving, Qualitative Process Theory, Qualitative Spatial Reasoning, Qualitative Temporal Reasoning, Self-explanatory Simulators, Surveys, Teleology
Papers on Reasoning Techniques
Papers on Sketch Understanding
Papers on Social Reasoning
Papers on Transfer Learning

Papers on Analogy and Similarity [back to the top]

Chang, M.D. (2014). Analogy Tutor: A Tutoring System for Promoting Conceptual Learning via Comparison. Doctoral Consortium, Twenty-Eighth AAAI Conference on Artificial Intelligence, Québec City, Québec, Canada.

Kandaswamy, S., Forbus, K., and Gentner, D. (2014). Modeling Learning via Progressive Alignment using Interim Generalizations. Proceedings of the Cognitive Science Society.

Liang, C. and Forbus, K. (2014). Constructing Hierarchical Concepts via Analogical Generalization.  Proceedings of the Cognitive Science Society.

Barbella, D. and Forbus, K. (2013). Analogical Word Sense DisambiguationAdvances in Cognitive Systems, 2:297-315.

Chang, M. D. and Forbus, K. D. (2013). Clustering Hand-Drawn Sketches via Analogical Generalization. Proceedings of the Twenty-Fifth Innovative Applications of Artificial Intelligence (IAAI-13), Bellevue, Washington.

Chang, M. D. and Forbus, K.D. (2012). Using Quantitative Information to Improve Analogical Matching Between Sketches. Proceedings of the 24th Annual Conference on Innovative Applications of Artificial Intelligence (IAAI). Toronto, Canada.

Friedman, S., Barbella, D., and Forbus, K. (2012). Repairing Qualitative Domain Knowledge with Cross-Domain Analogy. Proceedings of QR 2012.

Friedman, S., Barbella, D., and Forbus, K. (2012). Revising Domain Knowledge with Cross-Domain Analogy.  Advances in Cognitive Systems, 2, 13-24.

Kandaswamy, S. and Forbus, K. (2012). Modeling Learning of Relational Abstractions via Structural Alignment. Proceedings of the 34th Annual Conference of the Cognitive Science Society (CogSci). Sapporo, Japan.

Lovett, A., and Forbus, K. (2012). Modeling multiple strategies for solving geometric analogy problems. Proceedings of the 34th Annual Conference of the Cognitive Science Society. Sapporo, Japan.

Lovett, A. (2012). Spatial Routines for Sketches: A Framework for Modeling Spatial Problem-Solving. Doctoral dissertation, Northwestern University, Department of Electrical Engineering and Computer Science, Evanston, Illinois. [Dissertation]

Barbella, D. and Forbus, K. (2011). Analogical Dialogue Acts: Supporting Learning by Reading Analogies in Instructional Texts. Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence (AAAI 2011), San Francisco, CA.

Forbus, K., Usher, J., Lovett, A., Lockwood, K., and Wetzel, J. (2011).  CogSketch: Sketch understanding for Cognitive Science Research and for Education.  Topics in Cognitive Science, 3(4), pp 648-666.

Gentner, D., and Forbus, K. (2011). Computational models of analogy. WIREs Cognitive Science, 2. 266-276.

Klenk, M., Forbus, K., Tomai, E. and Kim, H. (2011). Using analogical model formulation with sketches to solve Bennett Mechanical Comprehension Test problems.  Journal of Experimental and Theoretical Artificial Intelligence, 23(3), pp. 299-327.

Lovett, A., and Forbus, K. (2011). Cultural commonalities and differences in spatial problem solving: A computational analysis.  Cognition 121, pp. 281-287.

Taylor, J. L. M., Friedman, S. E., Forbus, K. D., Goldwater, M. and Gentner, D. (2011). Modeling structural priming in sentence production via analogical processes. Proceedings of the 33rd Annual Conference of the Cognitive Science Society (CogSci). Boston, MA.

Barbella, D., and Forbus, K. (2010). Analogical dialogue acts: Supporting learning by reading analogiesProceedings NAACL HLT 2010: 1st Int. Workshop on Formalisms and Methodology for Learning by Reading.

Lovett, A., Forbus, K., and Usher, J. (2010). A structure-mapping model of Raven's Progressive Matrices. Proceedings of CogSci-10.

Dehghani, M., Gentner, D., Forbus, K., Ekhtiari, H., and Sachdeva, S., (2009). Analogy and moral decision making. In B. Kokinov, K. Holyoak and D. Gentner (Eds.) Proceedings of the Second International Conference on Analogy. NBU Press, Sofia, Bulgaria.

Gentner, D., Loewenstein, J., Thompson, L., and Forbus, K. (2009) Reviving inert knowledge: Analogical abstraction supports relational retrieval of past events. Cognitive Science, 3, 1343-1382.

Lockwood, K. (2009). Using Analogy to Model Spatial Language Use and Multimodal Knowledge Capture. Doctoral dissertation, Northwestern University, Department of Electrical Engineering and Computer Science, Evanston, Illinois. [Dissertation]

Lovett, A., Gentner, D., Forbus, K. and Sagi, E. (2009). Using analogical mapping to simulate time-course phenomena in perceptual similarity. Cognitive Systems Research, 10, 216-228.

Lovett, A., Sagi, E., Gentner, D. and Forbus, K. (2009). Modeling perceptual similarity as analogy resolves the paradox of difference detection. Proceedings of the 2nd International Analogy Conference. Sofia, Bulgaria.

Halstead, D. and Forbus, K. (2007). Some Effects of a Reduced Relational Vocabulary on the Whodunit Problem. Proceedings of IJCAI-2007, Hyderabad, India.

Lovett, A., Lockwood, K., Dehghani, M., and Forbus, K. (2007). Modeling human-like rates of learning via analogical generalization. Proceedings of Analogies: Integrating Multiple Cognitive Abilities. Nashville, Tennessee.

Lovett, A., Sagi, E., and Gentner, D. (2007). Analogy as a mechanism for comparison. Proceedings of Analogies: Integrating Multiple Cognitive Abilities. Nashville, Tennessee.

Dehghani, M. and Lovett, L. (2006) Efficient Genre Classification using Qualitative Representations. Proceedings of the 7th International Conference on Music Information Retrieval, Victoria, Canada.

Lovett, A., Gentner, D., and Forbus, K. (2006). Simulating Time-Course Phenomena in Perceptual Similarity via Incremental Encoding. Proceedings of the Twenty-Eighth Annual Meeting of the Cognitive Science Society.

Ouyang, T. and Forbus, K. (2006). Strategy variations in analogical problem solving. Proceedings of AAAI-06.

Halstead, D. and Forbus, K. (2005). Transforming between Propositions and Features: Bridging the Gap. Proceedings of AAAI-2005. Pittsburgh, PA.

Yan, J. and Forbus, K. (2005). Similarity-based qualitative simulation. Proceedings of the 27th Annual Meeting of the Cognitive Science Society.

Yan, J. and Forbus, K. (2004). Similarity-based qualitative simulation: A preliminary report. Proceedings of the 18th International Qualitative Reasoning Workshop, Evanston, Illinois, USA, August.

Yan, J., Forbus, K., and Gentner, D. (2003). A Theory of Rerepresentation in Analogical Matching. Proceedings of the Twenty-fifth Annual Meeting of the Cognitive Science Society.

Forbus, K., Mostek, T. and Ferguson, R. (2002). An analogy ontology for integrating analogical processing and first-principles reasoning. Proceedings of IAAI-02, July.

Nicholson, S. and Forbus, K. (2002). Answering comparison questions in SHAKEN: A progress report. AAAI Spring Symposium on Mining Answers from Texts and Knowledge Bases, Palo Alto, CA.

Forbus, K. (2001). Exploring analogy in the large. In Gentner, D., Holyoak, K., and Kokinov, B. (Eds.) Analogy: Perspectives from Cognitive Science. MIT Press.

Kuehne, S., Forbus, K., Gentner, D. and Quinn, B. (2000). SEQL: Category learning as progressive abstraction using structure mapping. Proceedings of CogSci 2000, August.

Kuehne, S., Gentner, D. and Forbus, K. (2000). Modeling infant learning via symbolic structural alignment. Proceedings of CogSci 2000, August.

Mostek, T., Forbus, K, and Meverden, C. (2000). Dynamic case creation and expansion for analogical reasoning. Proceedings of AAAI-2000. Austin, TX.

Forbus, K., Gentner, D., Everett, J. and Wu, M. (1997). Towards a computational model of evaluating and using analogical inferences. Proceedings of CogSci97.

Gentner, D., Brem, S., Ferguson, R.W., Markman, A.B., Levidow, B.B., Wolff, P., and Forbus, K. (1997). Analogical reasoning and conceptual change: A case study of Johannes Kepler. The Journal of the Learning Sciences, 6(1), 3-40.

Gentner, D. and Markman, A. (1997). Structure mapping in analogy and similarity. American Psychologist, January, 45-56.

Ferguson, R. and Forbus, K. (1995). Understanding Illustrations of Physical Laws by Integrating Differences in Visual and Textual Representations. AAAI Fall Symposium on Computational Models for Integrating Language and Vision.

Forbus, K., Gentner, D. and Law, K. (April-June, 1995). MAC/FAC: A model of Similarity-based Retrieval. Cognitive Science, 19(2), 141-205. [NB: the paper incorrectly identifes the year of publication as 1994]

Gentner, D., Rattermann, M.J., Markman, A., and Kotovsky, L. (1995). Two forces in the development of relational similarity.

Ferguson, R. W. (1994). MAGI: Analogy-based encoding using regularity and symmetry. In A. Ram and K. Eiselt (Eds.), Proceedings of the Sixteenth Annual Conference of the Cognitive Science Society (pp. 283-288). Atlanta, GA: Lawrence Erlbaum Associates.

Forbus, K., Ferguson, R. and Gentner, D. (1994). Incremental Structure-Mapping. Proceedings of the Sixteenth Annual Conference of the Cognitive Science Society, August.

Law, K. Forbus, K. and Gentner, D. (1994). Simulating similarity-based retrieval: A comparison of ARCS and MAC/FAC.  Proceedings of the Cognitive Science Society, August.

Gentner, D., Rattermann, M.J., and Forbus, K.D. (1993). The roles of similarity in transfer: Separating retrievability from inferential soundnessCognitive Psychology 25, 524-575.

Forbus, K. and Gentner, D. (1991). Similarity-based Cognitive Architecture. Proceedings of the AAAI Spring Symposium on Integrated Intelligent Architectures, March.

Gentner, D. and Forbus, K. (1991). MAC/FAC: A model of similarity-based retrieval. Proceedings of the Cognitive Science Society.

Gentner, D. and Boronat, C.B. (1991). Metaphors are (sometimes) processed as generative domain-mappings. (Unpublished Draft. Do not cite without permission).

Falkenhainer, B. (1990). Analogy in Context. DRAFT.

Falkenhainer, B. (1990). A unified approach to explanation and theory formation. In J. Shrager and P. Langley (Eds.), Computational models of scientific discovery and theory formation (pp. 157-196). Morgan Kaufmann Publishers.

Forbus, K. and Gentner, D. (1990). Similarity-based cognitive architecture.

Forbus, K. and Oblinger, D. (1990). Making SME greedy and pragmatic. Proceedings of the Cognitive Science Society.

Falkenhainer, B., Forbus, K. and Gentner, D. (1989). The Structure Mapping Engine: Algorithm and examples. Artificial Intelligence, 41, 1-63.

Forbus, K. and Gentner, D. (1989). Structural evaluation of analogies: What counts? Proceedings of the Cognitive Science Society.

Falkenhainer, B. (1988). Learning from physical analogies: A study in analogy and the explanation process. (Technical Report No. UIUCDCS-R-88-1479). University of Illinios at Urbana-Champaign. (Ph.D. Thesis)

Forbus, K. and Gentner, D. (1986). Learning Physical Domains: Towards a Theoretical Framework. In Michalski, R., Carbonell, J. and Mitchell, T. (Eds.), Machine Learning: An Artificial Intelligence Approach, Volume 2. Tioga press.

Falkenhainer, B., Forbus, K. and Gentner, D. (1986). The Structure-Mapping Engine. Proceedings of the Fifth National Conference on Artificial Intelligence.

Falkenhainer, B., Forbus, K. and Gentner, D. (1986). The Structure-Mapping Engine. (Tech. Rep. No. UIUCDCS-R-86-1275, UILU-ENG-86-1732). Urbana, Illinois: University of Illinois at Urbana-Champaign, Department of Computer Science.

Forbus, K. and Gentner, D. (1983). Learning Physical Domains:  Towards a theoretical framework. Proceedings of the 1983 International Machine Learning Workshop, Monticello, Illinois, June.

Papers on Companion Cognitive Systems [back to the top]

Friedman, S., Barbella, D., and Forbus, K. (2012). Repairing Qualitative Domain Knowledge with Cross-Domain Analogy. Proceedings of QR 2012.

Friedman, S., Barbella, D., and Forbus, K. (2012). Revising Domain Knowledge with Cross-Domain Analogy.  Advances in Cognitive Systems, 2, 13-24.

Hinrichs, T. and Forbus, K. (2012). Learning Qualitative Models by Demonstration. Proceedings of the 26th AAAI Conference on Artificial Intelligence, 207-213, July.

Friedman, S. E. and Forbus, K. D. (2010). An integrated systems approach to explanation-based conceptual change. Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence. Atlanta, GA.

Forbus, K, Klenk, M. and Hinrichs, T. (2009, July/August). Companion Cognitive Systems: Design Goals and Lessons Learned So Far. IEEE Intelligent Systems, 24(4), 36-46.

Klenk, M. and Forbus, K. D. (2009). Domain Transfer via Cross-Domain Analogy. Cognitive Systems Research, Special Issue on “Analogies: Integrating Cognitive Abilities”. Elsevier.

Forbus, K., Klenk, M. and Hinrichs, T. (2008). Companion Cognitive Systems: Design Goals and Some Lessons Learned. Proceedings of the AAAI Fall Symposium on Naturally Inspired Artificial Intelligence.

Klenk, M. and Forbus, K. (2007). Cognitive modeling of analogy events in physics problem solving from examples. Proceedings of CogSci-07. Nashville, TN.

Forbus, K. and Hinrichs, T. (2006). Companion Cognitive Systems: A step towards human-level AI. AI Magazine, 27(2), Summer, 83-95.

Forbus, K. (2005). Companion Cognitive Systems: An Overview. One-page abstract for invited Fellows Talk, 27th Annual Meeting of the Cognitive Science Society, Stresa, Italy.

Forbus, K., Usher, J. and Tomai, E. (2005). Analogical learning of visual/conceptual relationships in sketches. Proceedings of AAAI-05.

Klenk, K., Forbus, K., Tomai, E., Kim, H., and Kyckelhahn, B. (2005). Solving everyday physical reasoning problems by analogy using sketches. Proceedings of AAAI-05.

Forbus, K. and Hinrichs, T. (2004). Self-modeling in Companion Cognitive Systems: Current Plans. DARPA Workshop on Self-Aware Systems, Washington, DC.

Forbus, K. and Hinrichs, T. (2004). Companion Cognitive Systems: A step towards human-level AI. AAAI Fall Symposium on Achieving Human-level Intelligence through Integrated Systems and Research, October, Washington, DC.

Papers on Conceptual Learning [back to the top]

Chang, M.D. (2014). Analogy Tutor: A Tutoring System for Promoting Conceptual Learning via Comparison. Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, Québec City, Québec, Canada.

Liang, C. and Forbus, K. (2014). Constructing Hierarchical Concepts via Analogical Generalization.  Proceedings of the Cognitive Science Society.

Friedman, S. E. (2012). Computational Conceptual Change: An Explanation-Based Approach. Doctoral dissertation, Northwestern University, Department of Electrical Engineering and Computer Science, Evanston, Illinois. [Dissertation]

McLure, M. and Forbus, K. (2012). Encoding Strategies for Learning Geographical Concepts via Analogy. Proceedings of the 26th International Workshop on Qualitative Reasoning. Los Angeles, CA.

Friedman, S. E. and Forbus, K. D. (2011). Repairing Incorrect Knowledge with Model Formulation and Metareasoning. Proceedings of the 22nd International Joint Conference on Artificial Intelligence. Barcelona, Spain.

Friedman, S. E., Forbus, K. D. and Sherin, B. (2011). Constructing and revising commonsense science explanations: A metareasoning approach. Proceedings of the AAAI Fall Symposium on Advances in Cognitive Systems.

Friedman, S. E., Forbus, K. D. and Sherin, B. (2011). How do the seasons change? Creating and revising explanations via model formulation and metareasoning. Proceedings of the 25th International Workshop on Qualitative Reasoning. Barcelona, Spain.

Friedman, S. E. and Forbus, K. D. (2010). An integrated systems approach to explanation-based conceptual change. In proceedings of the 24th AAAI Conference on Artificial Intelligence. Atlanta, GA.

McLure, M., Friedman, S., and Forbus, K. (2010). Learning concepts from sketches via analogical generalization and near-misses. Proceedings of the 32nd Annual Conference of the Cognitive Science Society (CogSci). Portland, OR.

McLure, M., Friedman, S., and Forbus, K. (2010). Combining progressive alignment and near-misses to learn concepts from sketches. Proceedings of the 24th International Workshop on Qualitative Reasoning. Portland, OR.

Friedman, S., Taylor, J. and Forbus, K. (2009). Learning Naïve Physics Models by Analogical Generalization. Proceedings of the 2nd International Analogy Conference. Sofia, Bulgaria.

Friedman, S. and Forbus, K. (2009). Learning Naïve Physics Models and Misconceptions. Proceedings of the 31st Annual Conference of the Cognitive Science Society. Amsterdam, Netherlands.

Friedman, S., Forbus, K. and Taylor, J. (2009). Learning and Reasoning with Qualitative Models of Physical Behavior. Proceedings of the 23rd International Workshop on Qualitative Reasoning, 37-43. Ljubljana, Slovenia.

Friedman, S. and Forbus, K. (2008). Learning Causal Models via Progressive Alignment and Qualitative Modeling: A Simulation. Proceedings of the 30th Annual Conference of the Cognitive Science Society (CogSci). Washington, D.C.

Friedman, S. and Forbus, K. (2008). Learning Qualitative Causal Models via Generalization and Quantity Analysis. Proceedings of the 22nd International Workshop on Qualitative Reasoning. Boulder, CO.

Papers on Educational Software [back to the top]

Chang, M.D. (2014). Analogy Tutor: A Tutoring System for Promoting Conceptual Learning via Comparison. Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, Québec City, Québec, Canada.

Jee, B., Gentner, D., Uttal, D., Sageman, B., Forbus, K., Manduca, C., Ormand, C., Shipley, T., and Tikoff, B. (2014). Drawing on experience: How domain knowledge is reflected in sketches of scientific structures and processes. Research in Science Education.

Wetzel, J. (2014). Understanding and Critiquing Multi-Modal Engineering Design Explanations. Doctoral dissertation, Northwestern University, Department of Electrical Engineering and Computer Science, Evanston, Illinois. [Dissertation]

Chang, M. D. and Forbus, K. D. (2013). Clustering Hand-Drawn Sketches via Analogical Generalization. Proceedings of the Twenty-Fifth Innovative Applications of Artificial Intelligence (IAAI-13), Bellevue, Washington.

Horiguchi, T., Hirashima, T., and Forbus, K. (2012). A Model-Building Learning Environment with Explanatory Feedback to Erroneous Models. Proceedings of ITS-2012.

Wetzel, J. and Forbus, K. (2012). Teleological Representations for Multi-Modal Design Explanations. Proceedings of the 26th International Workshop on Qualitative Reasoning. Los Angeles, California.

Chang, M. D., Wetzel, J. and Forbus, K. D. (2011). Qualitative and Quantitative Reasoning over Physics Textbook Diagrams. Proceedings of the 25th International Workshop on Qualitative Reasoning. Barcelona, Spain.

Forbus, K., Usher, J., Lovett, A., Lockwood, K., and Wetzel, J. (2011).  CogSketch: Sketch understanding for Cognitive Science Research and for Education.  Topics in Cognitive Science, 3(4), pp 648-666.

Wetzel, J. and Forbus, K. (2010). Design Buddy: Providing Feedback for Sketched Multi-Modal Causal Explanations. Proceedings of the 24th International Workshop on Qualitative Reasoning. Portland, Oregon.

Yin, P., Forbus, K., Usher, J., Sageman, B. and Jee, B. (2010). Sketch Worksheets: A Sketch-based Educational Software System. Proceedings of the 22nd Annual Conference on Innovative Applications of Artificial Intelligence.

Forbus, K., Carney, K., Sherin, B. and Ureel, L. (2004). Qualitative modeling for middle-school students. Proceedings of the 18th International Qualitative Reasoning Workshop, Evanston, Illinois, August.

Forbus, K., Carney, K., Sherin, B. and Ureel, L. (2004). VModel: A visual qualitative modeling environment for middle-school students. Proceedings of the 16th Innovative Applications of Artificial Intelligence Conference, San Jose, July 2004.

Ureel, Leo and Carney, Karen (2003). Design Of Computational Supports for Students in Visual Modelling Tasks. In Wasson B., Baggetun, R., Hoppe, U., Ludvigsen, S. (Eds.) International Conference on Computer Support for Collaborative Learning, CSCL 2003, Community events, Communication and Interaction. (pp. 98-100) Bergen, Norway, University of Bergen Press.

Carney, Karen and Ureel, Leo (2003). Demonstration of Supports for Student Reuse and Integration of Knowledge through Modeling. In Wasson B., Baggetun, R., Hoppe, U., Ludvigsen, S. (Eds.) International Conference on Computer Support for Collaborative Learning, CSCL 2003, Community events, Communication and Interaction. (pp. 98-100) Bergen, Norway, University of Bergen Press.

Carney, K, Forbus K., Ureel, L., Sherin, B. (2002). Using Modeling to Support Integration and Reuse of Knowledge in School Science: Vmodel, a New Educational Technology. American Educational Research Association Annual Conference, April, 2002.

Carney, Karen, (2002). When is a Tree a Process? Influences on Student Representations of Process in "Low Floor" Qualitative Modeling Tasks. In P. Bell and T. Satwicz (Eds) Keeping Learning Complex: The Proceedings of the Fifth Annual International Conference of the Learning Sciences, (pp. 49-56) Mahwah, NJ: Lawrence Earlbaum.

Forbus, K. (2002). Helping children become qualitative modelers. Journal of the Japanese Society for Artificial Intelligence, 17(4), 471-479.

Forbus, K. (2001). Articulate software for science and engineering education. In Forbus, K., Feltovich, P., and Canas, A. (Eds.) Smart machines in education: The coming revolution in educational technology. AAAI Press.

Forbus, K., Carney, K., Harris, R. and Sherin, B. (2001). A qualitative modeling environment for middle-school students: A progress report. Proceedings of the 15th International Workshop on Qualitative Reasoning (QR01).

Forbus, K., Feltovich, P., and Canas, A. (Eds.) (2001). Smart Machines in Education: The coming revolution in educational technology. AAAI Press.

Forbus, K.D., Whalley, P., Everett, J., Ureel, L., Brokowski, M., Baher, J. and Kuehne, S. (1999). CyclePad: An articulate virtual laboratory for engineering thermodynamics. Artificial Intelligence, 114, 297-347.

Koedinger, K. R., Suthers, D. D., and Forbus, K. D. (1999).  Component-based construction of a science learning space: A model and feasibility demonstration.   Invited paper, International Journal of Artificial Intelligence in Education.

Forbus, K., Everett, J., Ureel, L., Brokowski, M., Baher, J., and Kuehne, S. (1998). Distributed Coaching for an Intelligent Learning Environment. Proceedings of QR98, May, Cape Cod.

Forbus, K. and Whalley, P. (1998).  Using qualitative physics to build articulate software for thermodynamics education: A preliminary reportInteractive Learning Environments, 1(1), 19-32.

Forbus, K. D. and Kuehne, S. E. (1998). RoboTA: An agent colony architecture for supporting education. Proceedings of the Second International Conference on Autonomous Agents (Agents '98). (pp. 455-456). Minneapolis/St. Paul, MN.

Koedinger, K. R., Suthers, D. D., and Forbus, K. D. (1998).  Component-based construction of a science learning space: A model and feasibility demonstration.  In Goettl, B. P., Halff, H. M., Redfield, C. L., and Shute, V. J. (Eds.) Intelligent Tutoring Systems, Proceedings of the Fourth International Conference, (pp. 166-175).  Lecture Notes in Computer Science, 1452.  Berlin: Springer-Verlag.

Forbus, K. (1997). Using qualitative physics to create articulate educational software. IEEE Expert, May/June, 32-41.

Forbus, K. and Whalley, P.B. (1994). Using qualitative physics to build articulate software for thermodynamics education. Proceedings of the 12th National Conference on Artificial Intelligence.

Papers on Intelligence Analysis [back to the top]

Wagner, E. J., Liu, J., Birnbaum, L. and Forbus, K.D. (2009). Rich Interfaces for Reading News on the Web. Proceedings of the 2009 International Conference on Intelligent User Interfaces (IUI 2009).   Slides PDF

Halstead, D. and Forbus, K. (2007). Some Effects of a Reduced Relational Vocabulary on the Whodunit Problem. Proceedings of IJCAI-2007, Hyderabad, India.

Birnbaum, L., Forbus, K., Wagner, E. J., Baker, J. and Witbrock, M. (2006). Analogy, Intelligent IR, and Knowledge Integration for Intelligence Analysis. 2005 AAAI Spring Symposium on AI Technologies for Homeland Security.

Kahlert, R. C., Rode, B., Baxter, D., Witbrock, M., Forbus, K., Birnbaum, L., Shah, P., Schneider, D., Panton, K., Belasco, A. and Crabbe, D. (2006). Tracking quantity fluctuations using STT. In the Proceedings of the 2006 AAAI Fall Symposium on Evidence Extraction, Arlington, VA.

Wagner, E. J., Liu, J., Birnbaum, L., Forbus, K. and James Baker (2006). Using Explicit Semantic Models to Track Situations Across News Articles. AAAI 2006 Workshop on Event Extraction and Synthesis.  Slides PDF

Forbus, K., Birnbaum, L., Wagner, E., Baker, J. and Witbrock, M. (2005). Analogy, intelligent IR, and knowledge integration: Situation tracking and the Whodunit problem. The 20005 International Conference on Intelligence Analysis. McLean, VA.

Papers on Interactive Entertainment [back to the top]

Blair, C. (2012). Qualitative Exploration in Freeciv. Master's Project Report, Northwestern University, Department of Electrical Engineering and Computer Science, Evanston, Illinois. [Master's Project Report]

Tomai, E. and Forbus, K. (2009). What are you going to do, talk me to death? Exploring the narrative state in interactive entertainment. AAAI Spring Symposium on Intelligent Narrative Technologies II. Palo Alto, CA.

Dunham, G., Forbus, K., and Usher, J. (2005). nuWar: A prototype sketch-based strategy game. Proceeding of the 1st Artificial Intelligence and Interactive Digital Entertainment Conference.

Forbus, K., and Kuehne, S. (2007). Episodic Memory: A Final Frontier (Abbreviated Version). Proceedings of AI for Interactive Digital Entertainment (AIIDE07), Palo Alto, CA.

Forbus, K., Mahoney, J., and Dill, K. (2001). How qualitative spatial reasoning can improve strategy game AIs. AAAI Spring Symposium on AI and Interactive Entertainment, March.

Forbus, K. and Wright, W. (2001). Some notes on programming objects in The Sims. Class notes from Northwestern's Computer Game Design course, 5/31/01.

Dobson, D. and Forbus, K. (1999). Towards articulate game engines. AAAI Spring Symposium on AI and computer games. (AAAI Technical Report SS-99-02).

Forbus, K. (1996). Why computer modeling should become a popular hobby. D-Lib Magazine, October.

Papers on Learning by Reading [back to the top]

Barbella, D. and Forbus, K. (2013). Analogical Word Sense DisambiguationAdvances in Cognitive Systems, 2:297-315.

Sharma, A. and Forbus, K.D. (2013). Automatic Extraction of Efficient Axiom Sets from Large Knowledge Bases. Proceedings of the Twenty-Seventh AAAI Conference on Artificial Intelligence (AAAI-13), Bellevue, Washington.

Sharma, A. and Forbus, K. (2012). Modeling the Evolution of Knowledge in Learning Systems. Proceedings of the Twenty-Sixth Conference on Artificial Intelligence (AAAI-12), Toronto, Canada.

Barbella, D. and Forbus, K. (2011). Analogical Dialogue Acts: Supporting Learning by Reading Analogies in Instructional Texts. Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence (AAAI 2011), San Francisco, CA.

Barbella, D., and Forbus, K. (2010). Analogical dialogue acts: Supporting learning by reading analogiesProceedings NAACL HLT 2010: 1st Int. Workshop on Formalisms and Methodology for Learning by Reading.

Forbus, K., Lockwood, K. and Sharma, A. (2009). Steps towards a 2nd generation learning by reading system. AAAI Spring Symposium on Learning by Reading, Spring 2009.

Lockwood, K. and Forbus, K. (2009). Multimodal knowledge capture from text and diagrams. Proceedings of KCAP-2009.

Forbus, K., Riesbeck, C., Birnbaum, L., Livingston, K., Sharma, A., and Ureel, L. (2007). Integrating Natural Language, Knowledge Representation and Reasoning, and Analogical Processing to Learn by Reading. Proceedings of AAAI-07: Twenty-Second Conference on Artificial Intelligence, Vancouver, BC.

Forbus, K., Lockwood, K., Tomai, E., Dehghani, M. and Czyz, J. (2007). Machine Reading as a Cognitive Science Research Instrument. AAAI Spring Symposium on Machine Reading. Stanford University, California.

Forbus, K., Riesbeck, C., Birnbaum, L., Livingston, K., Sharma, A., and Ureel, L. (2007). A Prototype System that Learns by Reading Simplified Texts. AAAI Spring Symposium on Machine Reading. Stanford University, California.

Forbus, K. D. and Kuehne, S. (2005). Towards a qualitative model of everyday political reasoning. Proceedings of the 19th International Qualitative Reasoning Workshop, Graz, Austria, May.

Ureel II, Leo C., K. Forbus, C. Riesbeck, and L. Birnbaum (2005). Question Generation for Learning by Reading. Proceedings of the AAAI Workshop on Textual Question Answering, Pittsburgh, Pennsylvania. July.

Papers on Natural Language Semantics [back to the top]

McFate, C.J., Forbus, K. and Hinrichs, T. (2014). Using Narrative Function to Extract Qualitative Information from Natural Language Texts. Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, Québec City, Québec, Canada.

McFate, C.J., Forbus, K.D., and Hinrichs, T.R. (2013). Using Narrative Function to Extract Qualitative Information from Natural Language Texts: A Preliminary Report. Proceedings of the 27th International Workshop on Qualitative Reasoning, Bremen, Germany.

McFate, C.J. and Forbus, K. (2011). NULEX: an open-license broad coverage lexicon. Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies: Short Papers, 2, 363-367.

Tomai, E. (2009). A Pragmatic Approach to Computational Narrative Understanding (Tech. Rep. No. NWU-EECS-09-17). Doctoral dissertation, Northwestern University, Department of Elecrtrical Engineering and Computer Science, Evanston, Illinois. [Dissertation]

Tomai, E. and Forbus, K. (2009). EA NLU: Practical Language Understanding for Cognitive Modeling. Proceedings of the 22nd International Florida Artificial Intelligence Research Society Conference. Sanibel Island, Florida.

Lockwood, K., Lovett, A., and Forbus, K. (2008). Automatic Classification of Containment and Support Spatial Relations in English and Dutch. Proceedings of Spatial Cognition.

Tomai, E. and Forbus, K. (2007, November). Narrative Presentation and Meaning. AAAI Fall Symposium on Intelligent Narrative Technologies, Arlington, VA.

Kuehne, S. E. (2004). On the Representation of Physical Quantities in Natural Language Text. Proceedings of the Twenty-sixth Annual Meeting of the Cognitive Science Society, Chicago, Illinois, August.

Kuehne, S. E. (2004). Understanding natural language descriptions of physical phenomena (Tech. Report NWU-CS-04-32). Doctoral dissertation, Northwestern University, Evanston, Illinois. [Dissertation]

Kuehne, S. and Forbus, K. (2004). Capturing QP-relevant information from natural language text. Proceedings of the 18th International Qualitative Reasoning Workshop, Evanston, Illinois, August.

Kuehne, S.E., and Forbus, K. D. (2002). Qualitative physics as a component in natural language semantics: A progress report. Proceedings of the Twenty-fourth Annual Meeting of the Cognitive Science Society, George Mason University, Fairfax, VA.

Papers on Ontology and Granular Partitions [back to the top]

Bittner, T. and Smith, B. (2001). Granular partitions and vagueness. Proceedings of the Conference on Formal Ontology in Information Systems (FOIS2001), ACM Press.

Bittner, T. and Smith, B. (2001). A taxonomy of granular partitions. Proceedings of the Conference on Spatial Information Theory (COSIT2001). Lecture Notes in Computer Science, Berlin-Heidelberg, Springer-Verlag.

Bittner, T. and Smith, B. (2001). A unified theory of granularity, vagueness and approximation. COSIT Workshop on Spatial Vagueness, Uncertainty, and Granularity.

Position Papers and Commentaries[back to the top]

Forbus, K. (2011). The Collaboration Game. Public Service Review: European Science and Technology, Issue 12, 49. (originally appeared in PSR).

Forbus, K., and Gentner, D. (2009). Dark knowledge in qualitative reasoning: A call to arms.Proceedings of QR09.

Price, C.J., Trave-massuyes, L., Milne, R., Ironi, I., Forbus, K., Bredeweg, B., Lee, M. Struss, P., Snooke, N., Lucas, P., Cavazza, M., Coghill, G. (2006).  Qualitative futures.  The Knowledge Engineering Review 21(4) pp 317-334.

Forbus, K., Gentner, D., Markman, A. and Ferguson, R. (1998). Analogy just looks like high level perception: Why a domain-general approach to analogical mapping is right. Journal of Experimental and Theoretical Artificial Intelligence (JETI), 10, 231-257.

Ferguson, R.W., Forbus, K.D., and Gentner, D. (1997). On the proper treatment of noun-noun metaphor: A critique of the Sapper model. Member abstract presented at the 19th Annual Meeting of the Cognitive Science Society, Stanford University, August. (HTML, PDF).

Forbus, K., Gentner, D., Markman, A. and Ferguson, R. (1997). Analogy just looks like high level perception: Why a domain-general approach to analogical mapping is right. Journal of Experimental and Theoretical Artificial Intelligence. (html version, PDF version). This paper is a reply to Chalmers, D. J., French, R. M., and Hofstadter, D. R. (1992). High-level perception, representation and analogy: A critique of artificial intelligence methodology. Journal of Experimental and Theoretical Artificial Intelligence, 4, 185-211.

Forbus, K. (1991). The physics of futures past: A response to Sacks and Doyle. Computational Intelligence.

Forbus, K. (1988). Intelligent Computer-Aided Engineering. AI Magazine.

Papers on Qualitative Reasoning

Common Sense Reasoning [back to the top]

Klenk, M., Forbus, K., Tomai, E. and Kim, H. (2011). Using analogical model formulation with sketches to solve Bennett Mechanical Comprehension Test problems.  Journal of Experimental and Theoretical Artificial Intelligence, 23(3), pp. 299-327.

Forbus, K., and Gentner, D. (2009). Dark knowledge in qualitative reasoning: A call to arms. Proceedings of QR09.

Paritsh, P. K. (2007). Back of the Envelope Reasoning for Robust Quantitative Problem Solving. (Tech. Rep. No. NWU-EECS-07-11). Doctoral dissertation, Northwestern University, Department of Elecrtrical Engineering and Computer Science, Evanston, Illinois. [Dissertation]

Paritosh, P.K. (2007). Beyond Corpus Lookup: Towards Heuristic Reasoning with Text. Proceedings of the 3rd International Workshop on Knowledge and Reasoning in Answering Questions, IJCAI-07, Hyderabad.

Paritosh, P. and Bridewell, W. (2007). From Whiteboard to Model: A Preliminary Analysis. Proceedings of the 21st International Workshop on Qualitative Reasoning, Aberystwyth, U.K.

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

Paritosh, P.K. (2006). The Heuristic Reasoning Manifesto. In Proceedings of the 20th International Workshop on Qualitative Reasoning, Hanover.

Paritosh, P. and Forbus, K. (2005). Analysis of Strategic Knowledge in Back of the Envelope Reasoning. Proceedings of the 20th National Conference on Artificial Intelligence (AAAI-05), Pittsburgh, PA.

Klenk, M., Forbus, K., Tomai, E., Kim,H., and Kyckelhahn, B. (2005). Solving Everyday Physical Reasoning Problems by Analogy using Sketches. Proceedings of 20th National Conference on Artificial Intelligence (AAAI-05), Pittsburgh, PA.

Paritosh, P.K. (2004). Symbolizing Quantity. In Proceedings of the 26th Cognitive Science Conference, Chicago.

Paritosh, P. and Forbus, K. (2004). Using strategies and AND/OR decomposition for back of the envelope reasoning. Proceedings of the 18th International Qualitative Reasoning Workshop, Evanston, Illinois, August.

Paritosh, P.K. (2003). A sketch of a theory of quantity. Proceedings of the 17th International Workshop on Qualitative Reasoning, Brasilia, Brazil, August 2003.

Paritosh, P.K. and Forbus, K.D. (2003). Qualitative Modeling and Similarity in Back of the Envelope Reasoning. Proceedings of the 25th Cognitive Science Conference, Boston, MA.

Paritosh, P.K. and Forbus, K.D. (2001). Common sense on the envelope. Proceedings of the 15th International Workshop on Qualitative Reasoning.

Forbus, K. and Gentner, D. (1997). Qualitative mental models: Simulations or memories? Proceedings of the Eleventh International Workshop on Qualitative Reasoning, Cortona, Italy, June 3-6, pp. 97-104.

Compositional Modeling [back to the top]

Forbus, K. (2010). Modeling Amidst the Microtheories. J. de Kleer and K. D. Forbus (Eds.), Proceedings of the 24th International Workshop on Qualitative Reasoning (112-115). Portland, OR.

Klenk, M., Friedman, S., and Forbus, K. (2008). Learning Modeling Abstractions via Generalization. Proceedings of the 22nd International Workshop on Qualitative Reasoning. Boulder, CO.

Xerox. (1991). Composition modeling of physical systems. (Report No. SSL-91-95, [P91-000181]). Palo Alto, CA: Falkenhainer, B. and Forbus, K.

Falkenhainer, B. and Forbus, K. (1988). Setting up Large-Scale Qualitative Models. Proceedings of the American Association for Artificial Intelligence (AAAI-88), St. Paul, MN, 301-306.

Engineering Problem Solving [back to the top]

Wetzel, J. (2014). Understanding and Critiquing Multi-Modal Engineering Design Explanations. Doctoral dissertation, Northwestern University, Department of Electrical Engineering and Computer Science, Evanston, Illinois. [Dissertation]

Chang, M. D., Wetzel, J. and Forbus, K. D. (2011). Qualitative and Quantitative Reasoning over Physics Textbook Diagrams. In proceedings of the 25th International Workshop on Qualitative Reasoning. Barcelona, Spain.

Sanghi, M., Paritosh P.K. and Thomas, R. (2005). Sub-linear Algorithms for Landmark Discovery from Black Box Models. In M. Hofbaur, B. Rinner and F. Wotawa (Eds.), Proceedings of the 19th International Workshop on Qualitative Reasoning (QR-05) (pp. 60). Graz, Austria: QR-05.

Sgouros, N. (1998). Interaction between physical and design knowledge in design from physical principles. Engineering Applications of Artificial Intelligence, 11, 449-459.

Pisan, Y. (1998). An integrated architecture for engineering problem solving. Doctoral dissertation, Northwestern University, Evanston, IL (Appendix of problems solved by the Thermodynamics Problem Solver). (UMI No. 733042431)

Pisan, Y. (1996). Using qualitative representations in controlling engineering problem solving. In Qualitative Reasoning Workshop (pp. 190-197). Stanford, California: QR-06. (html, Microsoft Word, Rich Text Format)

Collins, J.W. (1993). Process-based diagnosis: An approach to understanding novel failures (UIUCDCS-R-94-1846) Champaign-Urbana: University of Illinois. (Tech. Rep. No. 48). Evanston, Illinois: Northwestern University, The Institute for the Learning Sciences.

Sgouros, N. (1993). Representing physical and design knowledge in innovative design. Dissertation. (UMI Publication No. AAT 9433920. ProQuest document ID: 741138271). [This paper might also be seen under the following title: Representing physical and design knowledge in innovative engineering design].

Collins, J.W. (1991). Diagnosis as failure understanding (Tech. Rep. No. UIUCDCS-R-91-1699/UILU-ENG-91-1745). Urbana-Champaign, IL: University of Illinois at Urbana-Champaign, Department of Computer Science.

Falkenhainer, B. and Forbus, K. (1991). Compositional modeling: Finding the right model for the job. Artificial Intelligence, 51, 95-143.

Skorstad, G. (1991). Finding stable causal interpretations of equations (Tech. Rep. No. UIUCDCS-R-91-1654/Tech Rep. No. UILU-ENG-91-1701). Urbana-Champaign, IL: University of Illinois at Urbana-Champaign, Computer Science Department, Qualitative Reasoning Group.

DeCoste, D. and Collins, J.W. (1991). IQE: An incremental qualitative envisioner. Proceedings of the 5th International Workshop on Qualitative Reasoning about Physical Systems (pp. 58-70). Austin, Texas: QR-91.

DeCoste, D. (1991). Toward a qualitative theory of safety control: When and how to panic intelligently (Tech. Rep. No. 14). Evanston, IL: Northwestern University, The Institute for the Learning Sciences.

Collins, J.W. and Forbus, K. (1990). Molecular collections: An ontology for reasoning about fluids. Manuscript submitted for publication. DRAFT, do not cite.

DeCoste, D. (1990). Dynamic across-time measurement interpretation: Maintaining qualitative understandings of physical system behavior (Tech. Rep. No. UIUCDCS-R-90-1572/UILU-ENG-90-1710). Urbana-Champaign, IL: University of Illinois at Urbana-Champaign, Department of Computer Science.

DeCoste, D. (1990). Dynamic across-time measurement interpretation. In Proceedings of the Eighth National Conference on Artificial Intelligence: Vol. 51(1-3). Special issue: Qualitative reasoning about physical systems II, Boston, Masachusetts (pp. 273-341). Menlo Park, California: AAAI Press. (also appears in: Readings in Model-Based Diagnosis, editors Walter Hamscher et al., Morgan Kauffmann, 1992).

Skorstad, G. and Forbus, K. (1989). Qualitative and quantitative reasoning about thermodynamics. In Proceedings of the Eleventh Annual Conference of the Cognitive Science Society, Ann Arbor, Michigan (pp. 892-899). Hillsdale, NJ: Lawrence Erlbaum Associates.

Forbus, K. (1988). Intelligent computer-aided engineering. AI Magazine, 9(3), 23-36.

Forbus, K. and Stevens, A. (1981). Using Qualitative Simulation to Generate Explanations. Proceedings of the Third Annual Conference of the Cognitive Science Society (pp. 219-221). Berkeley, California.

Qualitative Process theory [back to the top]

McFate, C.J., Forbus, K. and Hinrichs, T. (2014). Using Narrative Function to Extract Qualitative Information from Natural Language Texts. Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, Québec City, Québec, Canada.  

McFate, C.J., Forbus, K.D., and Hinrichs, T.R. (2013). Using Narrative Function to Extract Qualitative Information from Natural Language Texts: A Preliminary Report. Proceedings of the 27th International Workshop on Qualitative Reasoning, Bremen, Germany.

Hinrichs, T. and Forbus, K. (2012). Toward Higher-Order Qualitative Representations. In Proceedings of the Twenty-sixth International Workshop on Qualitative Reasoning. Los Angeles CA, July.

Hinrichs, T., Forbus, K., de Kleer, J., Yoon, S., Jones, E., Hyland, R., and Wilson, J. (2011). Hybrid Qualitative Simulation of Military Operations. Proceedings of the 23rd Innovative Applications for Artificial Intelligence Conference, pp. 1655-1661, San Francisco, CA.

Chang, M. D., Wetzel, J. and Forbus, K. D. (2011). Qualitative and Quantitative Reasoning over Physics Textbook Diagrams. Proceedings of the 25th International Workshop on Qualitative Reasoning. Barcelona, Spain.

Forbus, K. (1989). Introducing actions into qualitative simulation. Proceedings of the 11th International Joint Conference on Artificial Intelligence, Vol. 2 (pp. 1273-1278). [Also Tech. Report No. UIUCDCS-R-88-1452]

Forbus, K. (1989). QPE: A study in assumption-based truth maintenance. International Journal of Artificial Intelligence in Engineering.

Hinrichs, T., Forbus, K., de Kleer, J., Yoon, S., Jones, E., Hyland, R. , and Wilson, J. (2010). Hybrid Qualitative Simulation of Military Operations. Proceedings of the 24th International Workshop on Qualitative Reasoning, August 8-10, Portland, Oregon, USA.

Dehghani, M. and Forbus, K. (2009). QCM: A QP-Based Concept Map System. Proceedings of the 23rd International Workshop on Qualitative Reasoning (pp. 16-21). Ljubljana, Slovenia: QR-09.

Forbus, K. (1993). Qualitative process theory: Twelve years after. Artificial Intelligence, 59, 115-123.

Collins, J. and Forbus, K.. (1989). Building qualitative models of thermodynamic processes. Proceedings of the Third International Workshop on Qualitative Reasoning (pp.?). Stanford, California: QR-03.

Forbus, K. (1989). Introducing actions into qualitative simulation. In Proceedings of the 11th International Joint Conference on Artificial Intelligence, Vol. 2 (pp. 1273-1278). [Also Tech. Report No. UIUCDCS-R-88-1452]

Forbus, K. (1988). QPE: Using assumption-based truth maintenance for qualitative simulation. The International Journal for Artificial Intelligence in Engineering, 3(4), 200-215.

Collins, J. and Forbus, K. (1987). Reasoning about fluids via molecular collections. Proceedings of the 6th National Conference on Artificial Intelligence (AAAI-87), Seattle Washington (pp. 590-594).

Forbus, K. (1987). Interpreting observations of physical systems. IEEE Transactions on Systems, Man, and Cybernetics, SMC-17(3), 350-359.

Forbus, K. (1987). The logic of occurrence. Proceedings of IJCAI-87, Milan, Italy, August.

Forbus, K. and Gentner,D. (1986). Causal reasoning about quantities. In Proceedings of the Eighth Annual Conference of the Cognitive Science Society (pp. 196-207). Amherst, Massachusetts: Lawrence Erlbaum & Associates.

Forbus, K. (1986). Interpreting measurements of physical systems. Proceedings of AAAI-86, Philadelphia, PA., August.

Forbus, K. (1986). The logic of occurrence. Proceedings of the 10th International Joint Conference on Artificial Intelligence.

Forbus, K. (1985). The problem of existence. (Tech. Rep. No. UIUCDCS-R-85-1239; UILU-ENG-85-1747). Urbana, Illinois: University of Illinois at Urbana-Champaign, Department of Computer Science.

Forbus, K. (1984). Qualitative process theory. Artificial Intelligence, 24, 85-168.

Forbus, K. (1983). Measurement interpretation in qualitative process theory. IJCAI-83.[The main text is more clear in this copy].

Forbus, K. (1982). Modelling motion with qualitative process theory. Proceedings of the Second National Conference on Artificial Intelligence, August.

Qualitative Spatial Reasoning [back to the top]

Lovett, A., and Forbus, K. (2013). Modeling spatial ability in mental rotation and paper-folding. Proceedings of the 35th Annual Conference of the Cognitive Science Society. Berlin, Germany, 930-935.

Chang, M. D., Wetzel, J. and Forbus, K. D. (2011). Qualitative and Quantitative Reasoning over Physics Textbook Diagrams. Proceedings of the 25th International Workshop on Qualitative Reasoning. Barcelona, Spain.

Lovett, A., and Forbus, K. (2011). Cultural commonalities and differences in spatial problem solving: A computational analysis.  Cognition 121, pp. 281-287.

Lovett, A., Lockwood, K., and Forbus, K. (2008). A computational model of the visual oddity task. Proceedings of the 30th Annual Conference of the Cognitive Science Society. Washington, D.C.

Lovett, A., Lockwood, K., and Forbus, K. (2008). Modeling cross-cultural performance on the visual oddity task. Proceedings of Spatial Cognition 2008. Freiburg, Germany.

Wetzel, J. and Forbus, K. (2008). Integrating Open-Domain Sketch Understanding with Qualitative Two-Dimensional Rigid-Body Mechanics. Proceedings of the 22nd International Workshop on Qualitative Reasoning. Boulder, CO.

Lovett, A. Forbus, K., and Usher, J. (2007). Analogy with qualitative spatial representations can simulate solving Raven's Progressive Matrices. Proceedings of the of the 29th Annual Conference of the Cognitive Science Society. Nashville, TN.

Lovett, A., Forbus, K., and Usher, J. (2007). Using qualitative representations and analogical mapping to solve problems from a spatial intelligence test. Proceedings of the 21st International Qualitative Reasoning Workshop. Aberystwyth, U.K.

Lockwood, K., Forbus, K., Halstead, D. and Usher, J. (2006). Automatic Categorization of Spatial Prepositions. Proceedings of the 28th Annual Conference of the Cognitive Science Society. Vancouver, Canada.

Lockwood, K., Forbus, K., and Usher, J. (2005). SpaceCase: A model of spatial preposition use. Proceedings of the 27th Annual Conference of the Cognitive Science Society. Stressa, Italy.

Tomai, E., Lovett, A., Forbus, K., and Usher, J. (2005). A Structure Mapping Model for Solving Geometric Analogy Problems. Proceedings of the 27th Annual Conference of the Cognitive Science Society, Stressa, Italy, 2190-2195.

Forbus, K., Mahoney, J.V., and Dill, K. (2002).  How qualitative spatial reasoning can improve strategy game AIs.  IEEE Intelligent Systems, July/August 2002.

Donlon, J.J. and Forbus, K. (2001).  Improving digital terrain with artificial intelligence.  Army AL&T, November-December 2001, 32-33.

Ferguson, R. and Forbus, K. (2000).  GeoRep: A flexible tool for spatial representation of line drawings.  Proceedings of AAAI-2000.  Austin, Texas.

Ferguson, R.W. and Forbus, K.D. (1999). GeoRep: A flexible tool for spatial representation of line drawings. Proceedings of the Qualitative Reasoning Workshop. Loch Awe, Scotland.

Donlon, J.J. and Forbus, K.D. (1999). Using a geographic information system for qualitative spatial reasoning about trafficability. Proceedings of the Qualitative Reasoning Workshop. Loch Awe, Scotland.

Mostek, T., Loewenstein, J., Forbus, K.D. and Gentner, D. (1999). Simulating the effects of relational language in spatial mapping abilities.  Proceedings of CogSci-99.

Pisan, Y. (1995). A visual routines based model of graph understanding. Proceedings of the 17th Annual Conference of the Cognitive Science Society.

Forbus, K. (1994). Qualitative spatial reasoning: Framework and frontiers. In: Glasgow, J ., Narayanan, H ., and Chandrasekaren, B. (Eds.), Diagrammatic Reasoning: Computational and Cognitive Perspectives, AAAI Press, 1995.

Pisan, Y. (1994). Visual reasoning with graphs. Qualitative Reasoning Workshop. (Visual reasoning about physical properties via graphs).

Kim, H. (1993). Qualitative reasoning about fluids and mechanics (Tech. Rep. No. 47). The Institute for the Learning Sciences, Northwestern University.

Forbus, K. (1992). Qualitative Spatial Reasoning: Framework and Frontiers. Proceedings of the AAAI Spring Symposium on Diagrammatic Representations, March.

Forbus, K., Nielsen, P., and Faltings, B. (1991). Qualitative spatial reasoning: The CLOCK project. Artificial Intelligence, 51(1-3), 417-471.

Hyun-Kyung, K. (1990). Qualitative kinematics of linkages (Tech Rep. No. UNCDCS-R-90-1603/ UILU-ENG-90-1742). Urbana, Illinois: University of Illinois at Urbana-Champaign, Department of Computer Science.

Nielsen, P.E. (1988). A qualitative approach to rigid body mechanics. (Tech. Rep. No. UIUCDCS-R-88-1469; UILU-ENG-88-1775). Urbana, Illinois: University of Illinois at Urbana-Champaign, Department of Computer Science.

Forbus, K., Nielsen, P., and Faltings, B. (1987). Qualitative kinematics: A framework. Proceedings of IJCAI-87, Milan, Italy, August.

Forbus, K. (1983). Qualitative reasoning about space and motion. In Gentner, D. and Stevens, A. (Eds.), Mental Models, LEA Associates, Inc., New Jersey.

Forbus, K. (1982). Modelling motion with qualitative process theory. Proceedings of the Second National Conference on Artificial Intelligence, August.

Forbus, K. (1981). Qualitative reasoning about physical processes. Proceedings of the seventh International Joint Conference on Artificial Intelligence, August.

Forbus, K. (1980). Spatial and qualitative aspects of reasoning about motion. Proceedings of the First National Conference on Artificial Intelligence (AAAI-'80), August. Stanford, California.

Qualitative Temporal Reasoning [back to the top]

Bittner, T. (2002). Approximate qualitative temporal reasoning. Annals of Mathematics and Artificial Intelligence, 35(1-2), 39-80.

Self-explanatory Simulators [back to the top]

Kyckelhahn, B. and Forbus, K. (2004). Jitter in self-explanatory simulation. Proceedings of the 18th International Qualitative Reasoning Workshop, Evanston, Illinois, August.

Forbus, K. (1996). Self-explanatory simulators for middle-school science education: A progress report. Proceedings of QR96.

Forbus, K. and Falkenhainer, B. (1995). Scaling up self-explanatory simulators: Polynomial-time compilation. Proceedings of IJCAI-95, Montreal, Canada.

Forbus, K. (1994). Polynomial-time compilation of self-explanatory simulators. Proceedings of QR94, Nara, Japan, June.

Forbus, K. (1994). Self-explanatory simulators: Making computers partners in the modeling process. Mathematics and Computers in Simulation, 36, 91-101.

Forbus, K. and Falkenhainer, B. (1992). Self-Explanatory Simulations: Scaling up to large models. Proceedings of AAAI 1992, San Jose, California, 685-690.

Forbus, K. (1991). Towards tutor compilers: Self-explanatory simulations as an enabling technology. Proceedings of the 1990 International Conference on the Learning Sciences, Northwestern University, Evanston, IL, 173-179.

Forbus, K. and Falkenhainer, B. (1990). Self-explanatory simulations: An integration of qualitative and quantitative knowledge. Proceedings of the American Association for Artificial Intelligence (AAAI-90).

Surveys [back to the top]

Forbus, K. (1996). Qualitative reasoning. CRC Hand-book of Computer Science and Engineering. CRC Press. (Next-to final drafts, with more citations than final version. Postscript)

Forbus, K. (1988). Qualitative physics: Past, present, and future. In Exploring Artificial Intelligence (pp. 239-296). San Francisco, California: Morgan-Kaufmann Publishers, Inc.

Teleology [back to the top]

Wetzel, J. and Forbus, K. (2012). Teleological Representations for Multi-Modal Design Explanations. Proceedings of the 26th International Workshop on Qualitative Reasoning. Los Angeles, California.

Everett, J. O. (1999). Topological inference of teleology: Deriving function from structure via evidential reasoning. Artificial Intelligence, 113 (1-2).

Everett, J. (1995). A theory of mapping from structure to function applied to engineering thermodynamics. Proceedings of the 14th International Joint Conference on Artificial Intelligence.

Forbus, K., Ferguson, R., Hyun, S., and Everett, J. (1993). Qualitative reasoning about function: A progress report. Submitted to AAAI Workshop on Reasoning About Function.

Papers on Reasoning Techniques [back to the top]

Hinrichs, T.R. and Forbus, K.D. (2013). Beyond the Rational Player: Amortizing Type-Level Goal Hierarchies. ACS-13 Workshop on Goal Reasoning, December.

Sharma, A. and Forbus, K.D. (2013). Automatic Extraction of Efficient Axiom Sets from Large Knowledge Bases. Proceedings of the Twenty-Seventh AAAI Conference on Artificial Intelligence (AAAI-13), Bellevue, Washington.

Sharma, A. and Forbus, K.D. (2013). Graph Traversal Methods for Reasoning in Large Knowledge-Based Systems. Proceedings of the Twenty-Seventh AAAI Conference on Artificial Intelligence (AAAI-13), Bellevue, Washington.

Sharma, A. (2011). Structural and Network-based methods for knowledge-based systems. Doctoral dissertation, Northwestern University, Department of Electrical Engineering and Computer Science, Evanston, Illinois. [Dissertation]

Forbus, K., Hinrichs, T., de Kleer, J., and Usher, J. (2010). FIRE: Infrastructure for Experience-based Systems with Common Sense. AAAI Fall Symposium on Commonsense Knowledge, Arlington, VA.

Sharma A. and Forbus, K. D. (2010). Graph-Based Reasoning and Reinforcement Learning for Improving Q/A Performance in Large Knowledge-Based Systems. AAAI Fall Symposium on Commonsense Knowledge, Arlington, VA.

Sharma A. and Forbus, K. D. (2010). Modeling the Evolution of Knowledge and Reasoning in Learning Systems. AAAI Fall Symposium on Commonsense Knowledge, Arlington, VA.

Everett, J. and Forbus, K. (1996). Scaling Up Logic-Based Truth Maintenance Systems via Fact Garbage Collection. Proceedings of the 13th National Conference on Artificial Intelligence.

Forbus, K. and de Kleer, J. (1993). Building Problem Solvers, MIT Press.

DeCoste, D. and Collins, J.W. (1991). CATMS: An ATMS which avoids label explosions. (Tech. Rep. No. 13). Evanston, IL: Northwestern University, The Institute for the Learning Sciences.

Forbus, K. and de Kleer, J. (1988). Focusing the ATMS. Proceedings of AAAI-88, August.

Papers on Sketch Understanding [back to the top]

Hinrichs, T. and Forbus, K. (2014). X Goes First: Teaching a Simple Game through Multimodal InteractionAdvances in Cognitive Systems, 3:31-46.

Jee, B., Gentner, D., Uttal, D., Sageman, B., Forbus, K., Manduca, C., Ormand, C., Shipley, T., and Tikoff, B. (2014). Drawing on experience: How domain knowledge is reflected in sketches of scientific structures and processes. Research in Science Education.

Wetzel, J. (2014). Understanding and Critiquing Multi-Modal Engineering Design Explanations. Doctoral dissertation, Northwestern University, Department of Electrical Engineering and Computer Science, Evanston, Illinois. [Dissertation]

Chang, M. D. and Forbus, K. D. (2013). Clustering Hand-Drawn Sketches via Analogical Generalization. Proceedings of the Twenty-Fifth Innovative Applications of Artificial Intelligence (IAAI-13), Bellevue, Washington.

Chang, M. D. and Forbus, K.D. (2012). Using Quantitative Information to Improve Analogical Matching Between Sketches. Proceedings of the 24th Annual Conference on Innovative Applications of Artificial Intelligence (IAAI). Toronto, Canada.

Lovett, A., Kandaswamy, S., McLure, M., and Forbus, K. (2012). Evaluating qualitative models of shape representation. Proceedings of the 26th International Workshop on Qualitative Reasoning. Los Angeles, CA.

Chang, M. D., Wetzel, J. and Forbus, K. D. (2011). Qualitative and Quantitative Reasoning over Physics Textbook Diagrams. Proceedings of the 25th International Workshop on Qualitative Reasoning. Barcelona, Spain.

Forbus, K., Usher, J., Lovett, A., Lockwood, K., and Wetzel, J. (2011).  CogSketch: Sketch understanding for Cognitive Science Research and for Education.  Topics in Cognitive Science, 3(4), pp 648-666.

Klenk, M., Forbus, K., Tomai, E. and Kim, H. (2011). Using analogical model formulation with sketches to solve Bennett Mechanical Comprehension Test problems.  Journal of Experimental and Theoretical Artificial Intelligence, 23(3), pp. 299-327.

Lovett, A. and Forbus, K. (2011). Organizing and representing space for visual problem-solving. Proceedings of the 25th International Workshop on Qualitative Reasoning. Barcelona, Spain.

McLure, M. D., Friedman, S. E., Lovett, A. and Forbus, K. D. (2011). Edge-cycles: A qualitative sketch representation to support recognition. Proceedings of the 25th International Workshop on Qualitative Reasoning. Barcelona, Spain.

Lovett, A. and Forbus, K. (2010). Shape is like space: Modeling shape representation as a set of qualitative spatial relations. Proceedings of the AAAI Spring Symposium on Cognitive Shape Processing. Palo Alto, CA.

McLure, M., Friedman, S., and Forbus, K. (2010). Learning concepts from sketches via analogical generalization and near-misses. Proceedings of the 32nd Annual Conference of the Cognitive Science Society (CogSci). Portland, OR.

McLure, M., Friedman, S., and Forbus, K. (2010). Combining progressive alignment and near-misses to learn concepts from sketches. Proceedings of the 24th International Workshop on Qualitative Reasoning. Portland, OR.

Wetzel, J. and Forbus, K. (2010). Design Buddy: Providing Feedback for Sketched Multi-Modal Causal Explanations. Proceedings of the 24th International Workshop on Qualitative Reasoning. Portland, Oregon.

Yin, P., Chang, M. D. and Forbus, K. D. (2010). Sketch-based Spatial Reasoning in Geologic Interpretation. Proceedings of the 24th International Workshop on Qualitative Reasoning. Portland, Oregon.

Yin, P., Forbus, K., Usher, J., Sageman, B. and Jee, B. (2010). Sketch Worksheets: A Sketch-based Educational Software System. Proceedings of the 22nd Annual Conference on Innovative Applications of Artificial Intelligence.

Jee, B., Gentner, D., Forbus, K., Sageman, B. and Uttal, D. (2009). Drawing on experience: Use of sketching to evaluate knowledge of spatial scientific concepts. Proceedings of the 31st Annual Conference of the Cognitive Science Society. Amsterdam, The Netherlands.

Lovett, A. and Forbus, K. (2009). Computing human-like qualitative topological relations via visual routines. Proceedings of the 23rd International Qualitative Reasoning Workshop. Ljubljana, Slovenia.

Lovett, A. and Forbus, K. (2009). Using a visual routine to model the computational of positional relations. Proceedings of the 31st Annual Conference of the Cognitive Science Society. Amsterdam, The Netherlands.

Lovett, A., Tomai, E., Forbus, K. and Usher, J. (2009). Solving geometric analogy problems through two-stage analogical mapping. Cognitive Science, 33(7), 1192-1231.

Wetzel, J. and Forbus, K. (2009). Automated Critique of Sketched Designs in Engineering. Proceedings of the 23rd International Workshop on Qualitative Reasoning. Ljubljana, Slovenia.

Wetzel, J. and Forbus, K. (2009). Automated Critique of Sketched Mechanisms. Proceedings of the 21st Innovative Applications of Artificial Intelligence Conference. Pasadena, California.

Forbus, K., Lovett, A., Lockwood, K., Wetzel, J., Matuk, C., Jee, B., and Usher, J. (2008). CogSketch. Demonstration description in the Proceedings of AAAI 2008.

Forbus, K., Usher, J., Lovett, A., Lockwood, K., and Wetzel, J. (2008). CogSketch: Open-domain sketch understanding for cognitive science research and for education. Proceedings of the Fifth Eurographics Workshop on Sketch-Based Interfaces and Modeling. Annecy, France.

Lockwood, K., Lovett, A., Forbus, K., Dehghani, M., and Usher, J. (2008). Automatic Interpretation of Depiction Conventions in Sketched Diagrams. Proceedings of the Eurographics Workshop on Sketch-Based Interfaces and Modeling.

Lockwood, K., Lovett, A., Forbus, K., Dehghani, M., and Usher, J. (2008). A Theory of Depiction for Sketches of Physical Systems. Proceedings of QR 2008.

Lovett, A., Dehghani, M., and Forbus, K. (2008). Building and comparing qualitative descriptions of three-dimensional design sketches. Proceedings of the 22nd International Qualitative Reasoning Workshop. Boulder, CO.

Wetzel, J., Forbus, K. (2008). Integrating Open-Domain Sketch Understanding with Qualitative Two-Dimensional Rigid-Body Mechanics. Proceedings of the 22nd International Workshop on Qualitative Reasoning. Boulder, CO.

Lovett, A., Dehghani, M. and Forbus, K. (2007). Constructing Spatial Representations of Variable Detail for Sketch Recognition. Proceedings of the AAAI Spring Symposium on Control Mechanisms for Spatial Knowledge Processing in Cognitive ⁄ Intelligent Systems, Stanford University, California.

Lovett, A., Dehghani, M. and Forbus, K. (2007). Incremental Learning of Perceptual Categories for Open-Domain Sketch Recognition. Proceedings of the International Joint Conferences on Artificial Intelligence, 447-452.

Lovett, A., Dehghani, M. and Forbus, K. (2006). Efficient Learning of Qualitative Descriptions for Sketch Recognition. Proceedings of the 20th International Qualitative Reasoning Workshop, Hanover, New Hampshire. July.

Forbus, K., Lockwood, K., Klenk, M., Tomai, E., and Usher, J. (2004). Open-domain sketch understanding: The nuSketch approach. Proceedings of the AAAI Fall Symposium on Making Pen-based Interaction Intelligent and Natural, October, Washington, DC.

Tomai, E., Forbus, K., and Usher, J. (2004). Qualitative spatial reasoning for geometric analogies. Proceedings of the 18th International Qualitative Reasoning Workshop, Evanston, Illinois, August.

Barker, K., Blythe, J., Borchardt, G., Chaudhri, V., Clark, P., Cohen, P., Fitzgerald, J., Forbus, K., Gil, Y., Katz, B., Kim, J., King, G., Mishra, S., Morrison, C., Murray, K., Otstott, C., Porter, B., Schrag, R., Uribe, T., Usher, J. and Yeh, P. (2003). A knowledge acquisition tool for course of action analysis. In Proceedings of the Innovative Applications of Artificial Intelligence Conference.

Forbus, K., Usher, J., and Chapman, V. (2003). Sketching for Military Courses of Action Diagrams. Proceedings of IUI'03, January, 2003. Miami, Florida.

Forbus, K., Usher, J. and Chapman, V. (2003). Qualitative spatial reasoning about sketch maps. Proceedings of the Fifteenth Annual Conference on Innovative Applications of Artificial Intelligence, Acapulco, Mexico.

Forbus, K., Tomai, E., and Usher, J. (2003). Qualitative spatial reasoning for visual grouping in sketches. Proceedings of the 17th International Workshop on Qualitative Reasoning, Brasilia, Brazil, August.

Forbus, K. and Usher, J. (2002). Sketching for knowledge capture: A progress report. IUI'02, January 13-16, San Francisco, California.

Rasch, R., Kott, Al, and Forbus, K. (2002). AI on the Battlefield: An experimental exploration. Proceedings of the 14th Innovative Applications of Artificial Intelligence Conference, July, Edmonton, Canada.

Forbus, K., Ferguson, R. and Usher, J. (2001). Towards a computational model of sketching. IUI'01,January 14-17, Santa Fe, New Mexico.

Ferguson, R. and Forbus, K. (2000).  GeoRep: A flexible tool for spatial representation of line drawings.  Proceedings of AAAI-2000.  Austin, Texas

Forbus, K. D., Ferguson, R. W. and Usher, J. M. (2000). Boundary-based multimodal input for geographic planning sketches. In P. Healy (Ed.), Proceedings of the First International Workshop on Interactive Graphical Communication. London: Queen Mary College, University of London.

Ferguson, R. W., Rasch, R. A. J., Turmel, W. and Forbus, K. D. (2000). Qualitative spatial interpretation of Course-of-Action diagrams. Proceedings of the 14th International Workshop on Qualitative Reasoning. Morelia, Mexico.

Forbus, K., Ferguson, R. and Usher, J. (2000). Towards a computational model of sketching. Proceedings of QR-2000, Morelia, Mexico.

Papers on Social Reasoning [back to the top]

Wilson, J.,  Forbus, K., and McClure, M. (2013). Am I Really Scared? A Multi-phase Computational Model of Emotions.  Proceedings of the 2nd Conference on Advances in Cognitive Systems.

Lovett, A., and Forbus, K. (2011). Cultural commonalities and differences in spatial problem solving: A computational analysis.  Cognition 121, pp. 281-287.

Dehghani, M. (2009). A Cognitive Model of Recognition-Based Moral Decision Making. Doctoral dissertation, Northwestern University, Department of Electrical Engineering and Computer Science, Evanston, Illinois. [Dissertation]

Dehghani, M., Gentner, D., Forbus, K., Ekhtiari, H., and Sachdeva, S., (2009). Analogy and moral decision making. In B. Kokinov, K. Holyoak & D. Gentner (Eds.) Proceedings of the Second International Conference on Analogy. NBU Press, Sofia, Bulgaria.

Dehghani, M., Sachdeva, S., Ekhtiari, H., Gentner D. and Forbus, K. (2009). The Role of Cultural Narratives in Moral Decision Making. Proceedings of the 31st Annual Conference of the Cognitive Science Society (CogSci), Washington, D.C.

Dehghani, M., Iliev, R. and Kaufmann, S. (2009). Causal Explanations in Counterfactual Reasoning. Proceedings of the 31st Annual Conference of the Cognitive Science Society, (CogSci).

Dehghani, M., Tomai, E., Forbus, K. and Klenk, M. (2008). Order of Magnitude Reasoning in Modeling Moral Decision-Making. Proceedings of the 22nd International Workshop on Qualitative Reasoning (QR). Boulder, CO.

Dehghani, M., Tomai, E., Forbus, K., Klenk, M. (2008). An Integrated Reasoning Approach to Moral Decision-Making. Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence (AAAI). Chicago, IL.

Dehghani, M., Tomai, E., Forbus, K., Iliev, R., 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.

Tomai, E., Forbus, K. (2008). Using Qualitative Reasoning for the Attribution of Moral Responsibility. Proceedings of the 30th Annual Conference of the Cognitive Science Society (CogSci). Washington, D.C.

Dehghani, M., Iliev, R. and Kaufmann, S. (2007). Effects of Fact Mutability in the Interpretation of Counterfactuals. Proceedings of the 29th Annual Conference of the Cognitive Science Society, Nashville, Tennessee.

Dehghani, M., Unsworth, S., Lovett, A. and Forbus, K. (2007). Capturing and Categorizing Mental Models of Food Webs using QCM. 21st International Workshop on Qualitative Reasoning, Aberystwyth, U.K.

Tomai, E. and Forbus, K. (2007). Plenty of Blame to Go Around: A Qualitative Approach to Attribution of Moral Responsibility. Proceedings of Qualitative Reasoning Workshop 2007, Aberystwyth, U.K.

Papers on Transfer Learning [back to the top]

Hinrichs, T. and Forbus, K. (2011). Transfer Learning Through Analogy in Games. AI Magazine, 32(1), 72-83.

Hinrichs, T. and Forbus, K. (2009). Learning game strategies by experimentation. Proceedings of the IJCAI-09 workshop on Learning Structural Knowledge from Observations. Pasadena, CA, July.

Klenk, M. (2009). Using Analogy to Overcome Brittleness in AI Systems (Tech. Rep. No. NWU-EECS-09-09). Doctoral dissertation, Northwestern University, Department of Elecrtrical Engineering and Computer Science, Evanston, Illinois. [Dissertation] [Online supplemental materials]

Klenk, M. and Forbus, K. (2009). Analogical Model Formulation for AP Physics Problems. Artificial Intelligence, 173(18), 1615-1638. doi:10.1016/j.artint.2009.09.003

Klenk, M. and Forbus, K. (2009). Persistent mappings in cross-domain analogical learning of physics domains. In Proceedings of the 2nd International Analogy Conference. Sofia, Bulgaria.

Hinrichs, T. and Forbus, K. (2007). Analogical Learning in a Turn-Based Strategy Game. Proceedings of the Twentieth International Joint Conference on Artificial Intelligence (pp. 853-858). Hyderabad, India.

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

Klenk, M. and Forbus, K. (2007). Learning domain theories via analogical transfer. Proceedings of Qualitative Reasoning Workshop 2007. Aberystwyth, U.K.

Klenk, M. and Forbus, K. (2007). Measuring the level of transfer learning by an AP Physics problem-solver. Proceedings of AAAI-07: Twenty-Second Conference on Artificial Intelligence, Vancouver, BC.

Klenk, M. and Forbus, K. (2006). Analogical Model Formulation for AP Physics Problems. 20th International Workshop on Qualitative Reasoning, Hanover, NH.

Hinrichs, T.R., Nichols, N.D. and Forbus, K.D. (2006). Using qualitative reasoning in learning strategy games: A preliminary report. 20th International Workshop on Qualitative Reasoning. Hanover, NH.

Gentner, D., Rattermann, M.J., and Forbus, K.D. (1993). The roles of similarity in transfer: Separating retrievability from inferential soundnessCognitive Psychology 25, 524-575.

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