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
Diagnostic reasoning based on structure and behavior
Artificial Intelligence - Special volume on qualitative reasoning about physical systems
The use of design descriptions in automated diagnosis
Artificial Intelligence - Special volume on qualitative reasoning about physical systems
Modeling digital circuits for troubleshooting
Artificial Intelligence - Special issue: Qualitative reasoning about physical systems II
Reasoning about linear circuits in sinusoidal steady state
Reasoning about linear circuits in sinusoidal steady state
Complex fans: a representation for vectors in polar form with interval attributes
ACM Transactions on Mathematical Software (TOMS)
Graph Theory With Applications
Graph Theory With Applications
Reasoning about linear circuits; a model-based approach
AI Communications
Measuring the level of transfer learning by an AP physics problem-solver
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
| Hi-index | 0.00 |
Modeling a system is the first step in reasoning about physical devices. By restricting our domain to linear circuits, we can find an efficient algorithm to solve that task.The algorithm presented in this article is an efficient implementation of the star‐mesh reductions used in Electrical Engineering. By choosing the right representation and based on simple data structures, we can reduce considerably the process of modeling a circuit.The algorithm has three main sources of efficiency gain: An efficient cluster representation reduces the complexity of the produced model; a simple data structure reduces the search for parallel regions; in the last step, we generate a circuit model where the principle of superposition does not need to be applied. Those three points reduce dramatically both the complexity of the modeling process and the size of the model. The reduction in the size of the model favorably impacts its use in any reasoning task to be performed. Finally, avoiding superposition will allow us to treat this class of circuits more efficiently.