Abstract
Understanding conceptual change is an important problem in modeling human cognition and in making integrated AI systems that can learn autonomously. This paper describes a model of explanation-based conceptual change, integrating sketch understanding, analogical processing, qualitative models, truth-maintenance, and heuristic-based reasoning within the Companions cognitive architecture. Sketch understanding is used to automatically encode stimuli in the form of comic strips. Qualitative models and conceptual quantities are constructed for new phenomena via analogical reasoning and heuristics. Truth-maintenance is used to integrate conceptual and episodic knowledge into explanations, and heuristics are used to modify existing conceptual knowledge in order to produce better explanations. We simulate the learning and revision of the concept of force, testing the concepts learned via a questionnaire of sketches given to students, showing that our model follows a similar learning trajectory.
Original language | English (US) |
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Title of host publication | AAAI-10 / IAAI-10 - Proceedings of the 24th AAAI Conference on Artificial Intelligence and the 22nd Innovative Applications of Artificial Intelligence Conference |
Pages | 1523-1529 |
Number of pages | 7 |
Volume | 3 |
State | Published - Nov 1 2010 |
Event | 24th AAAI Conference on Artificial Intelligence and the 22nd Innovative Applications of Artificial Intelligence Conference, AAAI-10 / IAAI-10 - Atlanta, GA, United States Duration: Jul 11 2010 → Jul 15 2010 |
Other
Other | 24th AAAI Conference on Artificial Intelligence and the 22nd Innovative Applications of Artificial Intelligence Conference, AAAI-10 / IAAI-10 |
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Country/Territory | United States |
City | Atlanta, GA |
Period | 7/11/10 → 7/15/10 |
ASJC Scopus subject areas
- Software
- Artificial Intelligence