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Personal profile

Education/Academic qualification

PhD, Massachusetts Institute of Technology

… → 1984

Fingerprint Dive into the research topics where Kenneth D Forbus is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

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Cognitive systems Engineering & Materials Science
Physics Engineering & Materials Science
Students Engineering & Materials Science
Experiments Engineering & Materials Science
Learning systems Engineering & Materials Science
Education Engineering & Materials Science
Semantics Engineering & Materials Science
Processing Engineering & Materials Science

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Grants 2000 2021

learning environment
university teacher
visualization
student
education
Intelligent agents
Intelligent systems
Learning systems
Decision support systems
Teaching
Apprentices
Intelligent systems
Demonstrations
Decision making
Semantics
Cognitive systems
Technical presentations
Students
Visibility
Artificial intelligence

Research Output 1978 2018

Action recognition from skeleton data via analogical generalization over qualitative representations

Chen, K. & Forbus, K. D., Jan 1 2018, 32nd AAAI Conference on Artificial Intelligence, AAAI 2018. AAAI press, p. 638-645 8 p. (32nd AAAI Conference on Artificial Intelligence, AAAI 2018).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Learning systems
Feature extraction
Pipelines

Bootstrapping from Language in the Analogical Theory of Mind Model

Rabkina, I., McFate, C. & Forbus, K. D., 2018, CogSci 2018 Proceedings: changing/minds. Kalish, C., Rau, M., Zhu, J. & Rogers, T. (eds.). p. 924-929 6 p.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Theory of Mind
Bootstrapping
Language
Interaction
Psychologists

Integrating Sketch Worksheets into GIFT

Forbus, K. D., Hinrichs, T. R., Hill, S. & Usher, M., 2018, Proceedings of the 6th Annual GIFT Users Symposium (GIFTSym6). Sottilare, R. (ed.). p. 87-93 7 p.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Learning from unannotated QA pairs to analogically disambiguate and answer questions

Crouse, M., McFate, C. & Forbus, K. D., Jan 1 2018, 32nd AAAI Conference on Artificial Intelligence, AAAI 2018. AAAI press, p. 654-662 9 p. (32nd AAAI Conference on Artificial Intelligence, AAAI 2018).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Semantics
Artificial intelligence

Learning to Build Qualitative Scenario Models From Natural Language

Crouse, M., McFate, C. & Forbus, K. D., 2018, Proceedings of the QR’18. Falomir, Z., Coghill, G. M. & Pang, W. (eds.). p. 32-39 8 p.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Decision making
Experiments