A qualitative physics based on confluences
Artificial Intelligence - Special volume on qualitative reasoning about physical systems
Artificial Intelligence
Artificial intelligence (3rd ed.)
Artificial intelligence (3rd ed.)
Applied system identification
Automatic control systems (7th ed.)
Automatic control systems (7th ed.)
Reasoning about nonlinear system identification
Artificial Intelligence
Intelligent Data Analysis: An Introduction
Intelligent Data Analysis: An Introduction
Global solutions for nonlinear systems using qualitative reasoning
Annals of Mathematics and Artificial Intelligence
Reasoning about Input-Output Modeling of Dynamical Systems
IDA '99 Proceedings of the Third International Symposium on Advances in Intelligent Data Analysis
Automating input-output modeling of dynamic physical systems
Automating input-output modeling of dynamic physical systems
Generalized physical networks for automated model building
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
Automated mathematical modeling from experimental data: anapplication to material science
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
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This paper describes a tool called Isaac (intelligent sensor analysis and actuator controller) that autonomously explores the behavior of a dynamical system and uses the resulting knowledge to help build and test mathematical models of that system. ISAAC is a unified knowledge representation and reasoning framework for input/output modeling that can be incorporated into any automated tool that reasons about dynamical models. It is based on two modeling paradigms, intelligent sensor data analysis and qualitative bifurcation analysis, which capture essential parts of an engineer's reasoning about modeling problems. We demonstrate ISSAC's power and adaptability by incorporating it into the Pret automated system identification tool and showing how input/ output modeling expands PRET's repertoire.