A qualitative physics based on confluences
Artificial Intelligence - Special volume on qualitative reasoning about physical systems
Artificial Intelligence
Qualitative physics using dimensional analysis
Artificial Intelligence
Causality and model abstraction
Artificial Intelligence
Metamodelling: for bond graphs and dynamic systems
Metamodelling: for bond graphs and dynamic systems
Computational and physical causality
IJCAI'91 Proceedings of the 12th international joint conference on Artificial intelligence - Volume 2
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This paper is a refined version of the work that the authors presented at the 13th International Workshop on Qualitative Reasoning, jointly with the late Dr Rob Milne. It is dedicated to Rob in recognition of his significant contribution and support for the research described herein. The paper presents a novel approach for generating causal dependencies between system variables, from an acausal description of the system behaviour, and for identifying the end causal impact, in terms of whether a change in the value of an influencing variable will lead to an increase or a decrease in the value of the influenced variables. This work is based on the use of the conventional method for dimensional analysis developed in classical physics, in conjunction with the exploitation of general heuristics. The utility of the work is demonstrated with its application to providing causal explanation for a benchmark problem that involves a dynamic feedback loop. The results reflect well the common-sense understanding of the causality in such a system that is otherwise difficult to capture using conventional causal ordering methods.