A Compositional Approach to Causality
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Citation: T. K. Satish Kumar. (2000) A Compositional Approach to Causality. In Proceedings of the Fourth International Symposium on Abstraction, Reformulation and Approximation (SARA2000), 2000.
| Publication inproceedings ( Edit ) | |
| type | InProceedings |
| bibtype | inproceedings |
| Bibtex basics | |
| author | T. K. Satish Kumar |
| title | A Compositional Approach to Causality |
| booktitle | Proceedings of the Fourth International Symposium on Abstraction, Reformulation and Approximation (SARA2000) |
| address | Austin, Texas |
| year | 2000 |
| Bibtex more | |
| Access Paper | |
| abstract | Inferring causality from equation models characterizing engineering domains is important towards predicting and diagnosing system behavior. Most previous attempts in this direction have failed to recognize the key differences between equations which model physical phenomena and those that just express rationality or numerical conveniences of the designer. These different types of equations bear different causal implications among the model parameters they relate. We show how unstructured and ad hoc formulations of equation models for apparent numerical conveniences are lossy in the causal information encoding and justify the use of CML as a model formulation paradigm which retains these causal structures among model parameters by clearly separating equations corresponding to phenomena and rationality. We provide an algorithm to infer causality from the active model fragments by using the notion of PreCondition graphs. |
| KSL Technical Report ID: KSL-00-04 |
Facts about A Compositional Approach to CausalityRDF feed
| Abstract | Inferring causality from equation models c … Inferring causality from equation models characterizing engineering domains is important towards predicting and diagnosing system behavior. Most previous attempts in this direction have failed to recognize the key differences between equations which model physical phenomena and those that just express rationality or numerical conveniences of the designer. These different types of equations bear different causal implications among the model parameters they relate. We show how unstructured and ad hoc formulations of equation models for apparent numerical conveniences are lossy in the causal information encoding and justify the use of CML as a model formulation paradigm which retains these causal structures among model parameters by clearly separating equations corresponding to phenomena and rationality. We provide an algorithm to infer causality from the active model fragments by using the notion of PreCondition graphs. y using the notion of PreCondition graphs. |
| Address | Austin, Texas + |
| Author | T. K. Satish Kumar + |
| Bibtype | inproceedings + |
| Booktitle | Proceedings of the Fourth International Symposium on Abstraction, Reformulation and Approximation (SARA2000) + |
| Has author | T. K. Satish Kumar + |
| Has identifier | KSL-00-04 + |
| Has publishing details | 2000 + |
| Has title | A Compositional Approach to Causality + |
| Has where published | Proceedings of the Fourth International Symposium on Abstraction, Reformulation and Approximation (SARA2000) + |
| Has year | 2000 + |
| Ksl tr id | KSL-00-04 + |
| Process note | NO + |
| Title | A Compositional Approach to Causality + |
| Year | 2000 + |
