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AN ARTIFICIAL NETWORK FOR REASONING IN THE CANCELLATION CLASS WITH APPLICATION TO THE DIAGNOSIS OF CELLS DIVISION

LOTFI BEN ROMDHANE

Department of Computer Sciences, Faculty of Sciences of Monastir, University of Monastir, Tunisia

https://doi.org/10.1142/S0218488505003473Cited by:0 (Source: Crossref)

Abstract

Causal reasoning is a hard task that cognitive agents perform reliably and quickly. A particular class of causal reasoning that raises several difficulties is the cancellation class. Cancellation occurs when a set of causes (hypotheses) cancel each other's explanation with respect to a given effect (observation). For example, a cloudy sky may suggest a rainy weather; whereas a shiny sky may suggest the absence of rain. In this work we extend a recent neural model to handle cancellation interactions. Simulation results are very satisfactory and should encourage research.

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