Artificial Intelligence - Special volume on qualitative reasoning about physical systems
Commonsense reasoning about causality: deriving behavior from structure
Artificial Intelligence - Special volume on qualitative reasoning about physical systems
Qualitative reasoning about physical systems
Qualitative reasoning about physical systems
Understanding text with an accompanying diagram
IEA/AIE '88 Proceedings of the 1st international conference on Industrial and engineering applications of artificial intelligence and expert systems - Volume 2
Understanding coreference in a system for solving physics word problems
Understanding coreference in a system for solving physics word problems
A model-based representational framework for expert physics problem solving
A model-based representational framework for expert physics problem solving
Computer Understanding of Physics Problems Stated in Natural Language.(Dissertation), also Technical Report NL-30
Physics Problem Solving Using Multiple Views
Physics Problem Solving Using Multiple Views
Reasoning about assumptions in graphs of models
IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 2
The abstraction/implementation model of problem reformulation
IJCAI'87 Proceedings of the 10th international joint conference on Artificial intelligence - Volume 2
Prompt: an innovative design tool
AAAI'87 Proceedings of the sixth National conference on Artificial intelligence - Volume 2
Understanding natural language with diagrams
AAAI'90 Proceedings of the eighth National conference on Artificial intelligence - Volume 1
Enabling experts to build knowledge bases from science textbooks
Proceedings of the 4th international conference on Knowledge capture
International Journal of Artificial Intelligence in Education
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A computer program, APEX, is proposed to investigate idealized formal models representing physics problems. Two types of models are defined: canonical physical objects and physical models. During problem solving, the problem is represented as a data connection network, which is progressively augmented by these models in the form of additional network elements. APEX employs views as a representational framework for connecting the initially informal objects to the formal models of the domain. The view framework supports multiple representations (e.g., viewing many objects as a single canonical physical object), handling of incompletely specified problems, and invertibility of the views. This computational framework provides a powerful representational mechanism that allows a finite set of physical principles to be applied to a potentially infinite variety of problems. As a knowledge engineering technique, views allow general principles to be applied to a variety of objects whose representations differ.