A qualitative physics based on confluences
Artificial Intelligence - Special volume on qualitative reasoning about physical systems
Qualitative analysis of MOS circuits
Artificial Intelligence - Special volume on qualitative reasoning about physical systems
Introduction to Operation Systems Design
Introduction to Operation Systems Design
Reasoning about discontinuous change
AAAI'87 Proceedings of the sixth National conference on Artificial intelligence - Volume 2
Reasoning about discontinuous change
AAAI'87 Proceedings of the sixth National conference on Artificial intelligence - Volume 2
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Two notions of process have been used in programs that reason about change* discrete models, which represent changes as instantaneous, and continuous models, which represent changes as processes that act gradually over time. We describe a technique called aggregation which unifies the two types of models and allows both to be used when performing qualitative simulation. Aggregation is a technique for recognizing cycles of processes and generating a continuous process that is equivalent to each cycle. A qualitative simulator may start prediction with a simple discrete model and use aggregation to generate a continuous process model when discrete simulation bogs down in a cycle. Aggregation thereby allows a simulator to switch back and forth between different types of models depending on which type is most expedient. To test these ideas, we have written a program, PEPTIDE, which performs qualitative simulation in the domain of molecular genetics. The flexibility of PEPTIDE'S aggregator allows the program to detect cycles within cycles and predict the behavior of complex situations.