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A neural network model of causality

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1 Author(s)
Ron Sun ; Dept. of Comput. Sci., Alabama Univ., Tuscaloosa, AL, USA

This paper proposes a model for commonsense causal reasoning, based on the basic idea of neural networks. After an analysis of the advantages and limitations of existing accounts of causality, a fuzzy logic based formalism FEL is proposed that takes into account the inexactness and the cumulative evidentiality of commonsense causal reasoning, overcoming the limitations of existing accounts. Analyses concerning how FEL handles various aspects of commonsense causal reasoning are performed, in an abstract way. FEL can be implemented (naturally) in a neural (connectionist) network. This work also serves to link rule-based reasoning with neural network models, in that a rule-encoding scheme (FEL) is equated directly to a neural network model

Published in:

Neural Networks, IEEE Transactions on  (Volume:5 ,  Issue: 4 )

Date of Publication:

Jul 1994

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