Representing Causality Using Fuzzy Cognitive Maps

Causal reasoning occupies a central position in human reasoning. In order to algorithmically consider causal relations, the relations must be placed into a representation that supports manipulation. The most widespread causal representation is directed acyclic graphs (DAGs). However, DAGs are severe...

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Bibliographic Details
Main Author: Mazlack, L.J.
Format: Conference Proceeding
Language:English
Subjects:
Association rules
causality
cognitive maps
commonsense
complexes
Computational intelligence
DAGs
Data analysis
Data mining
fuzzy
Fuzzy cognitive maps
Fuzzy reasoning
Humans
imprecision
Information processing
Laboratories
Marketing and sales
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Summary:Causal reasoning occupies a central position in human reasoning. In order to algorithmically consider causal relations, the relations must be placed into a representation that supports manipulation. The most widespread causal representation is directed acyclic graphs (DAGs). However, DAGs are severely limited in what portion of the common sense world they can represent. This paper considers the needs of commonsense causality and suggests Fuzzy Cognitive Maps as an alternative to DAGs.
DOI:10.1109/NAFIPS.2009.5156434