A qualitative physics based on confluences
Artificial Intelligence - Special volume on qualitative reasoning about physical systems
Artificial Intelligence - Special volume on qualitative reasoning about physical systems
Artificial Intelligence
Artificial Intelligence
Theories of causal ordering: reply to de Kleer and Brown
Artificial Intelligence
Theories of comparative analysis
Theories of comparative analysis
Readings in qualitative reasoning about physical systems
Readings in qualitative reasoning about physical systems
Combining Dimensional Analysis and Heuristics for Causal Ordering--In Memory of Dr Rob Milne --
Proceedings of the 2006 conference on Rob Milne: A Tribute to a Pioneering AI Scientist, Entrepreneur and Mountaineer
Generating explanations of device behavior using compositional modeling and causal ordering
AAAI'93 Proceedings of the eleventh national conference on Artificial intelligence
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Causality plays an important role in qualitative reasoning about physical systems. In this paper we show that the bond-graph method can be fruitfully applied to represent and generate causal order on a formal basis. Both physical and computational aspects of bond-graph causality are discussed. In particular we show that it provides a (inner physical foundation for a causal order along the lines of Iwasaki and Simon. Bond-graph causality also generates more information than does the causal ordering theory, including better causal resolution, an improved definition of exogeneity in terms of parameters and sources, automatic checking of self containment, and a more detailed, physical treatment of feedback.