Intelligence in scientific computing
Communications of the ACM
Practical numerical algorithms for chaotic systems
Practical numerical algorithms for chaotic systems
Geometric structures for three-dimensional shape representation
ACM Transactions on Graphics (TOG)
KAM: Automatic Planning and Interpretation of Numerical Experiments Using Geometrical Methods
KAM: Automatic Planning and Interpretation of Numerical Experiments Using Geometrical Methods
Self-explanatory simulations: scaling up to large models
AAAI'92 Proceedings of the tenth national conference on Artificial intelligence
Generating quasi-symbolic representation of three-dimensional flow
AAAI'93 Proceedings of the eleventh national conference on Artificial intelligence
A qualitative method to construct phase portraits
AAAI'93 Proceedings of the eleventh national conference on Artificial intelligence
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We develop a qualitative method for understanding and representing phase space structures of complex systems. To demonstrate this method, a program called MAPS has been constructed that understands qualitatively different regions of a phase space and represents and extracts geometric shape information about these regions, using deep domain knowledge of dynamical system theory. Given a dynamical system specified as a system of governing equations, MAPS applies a successive sequence of operations to incrementally extract the qualitative information and generates a complete, high level symbolic description of the phase space structure, through a combination of numerical, combinatorial, and geometric computations and spatial reasoning techniques. The high level description is sensible to human beings and manipulable by other programs. We are currently applying the method to a difficult engineering design domain in which controllers for complex systems are to be automatically synthesized to achieve desired properties, based on the knowledge of the phase space "shapes" of the systems.