Presentation	1999/5/28 Causal Modeling through Factorial Representation Kazunori Watase,
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Abstract(in English)	Blalock proposed the methods that obtained a causal model through thinking experiment. However these methods become difficult to apply as the variables increase. Furthermore, it is impossible often to specify the model from only correlation coefficients. Therefore, the knowledge regarding the order relations between variables is required to make a model. In model research, the order relations have to be considered. So, in this paper, we represent a permutation by a factorial scale. AS a result, it is possible to search models remaining order relations and to enumerate permutations that satisfy order conditions. Also, we understood that the factorial representations could be applied in simulated annealing.
Keyword(in Japanese)	(See Japanese page)
Keyword(in English)	causal modeling / factorial representation / enumeration / heuristic
Paper #	AI99-19
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Conference Information
Committee	AI
Conference Date	1999/5/28(1days)
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Paper Information
Registration To	Artificial Intelligence and Knowledge-Based Processing (AI)
Language	JPN
Title (in Japanese)	(See Japanese page)
Sub Title (in Japanese)	(See Japanese page)
Title (in English)	Causal Modeling through Factorial Representation
Sub Title (in English)
Keyword(1)	causal modeling
Keyword(2)	factorial representation
Keyword(3)	enumeration
Keyword(4)	heuristic
1st Author's Name	Kazunori Watase
1st Author's Affiliation	Nagasaki Institute of Applied Science()
Date	1999/5/28
Paper #	AI99-19
Volume (vol)	vol.99
Number (no)	96
Page	pp.pp.-
#Pages	8
Date of Issue