Automatically assigned DDC number:

Manually assigned DDC number: 00633

Number of references: 0

Title: Verification and Validation of KBS With Neural Network Components

Author:

Author:

Subject: Wu Wen,John Callahan Verification and Validation of KBS With Neural Network Components

Description: Artificial Neural Networks(ANN) play an important role in developing robust Knowledge Based Systems(KBS). The ANN based components used in these systems learn to give appropriate predictions through training with correct input-output data patterns. Unlike traditional KBS that depends on a rule database and a production engine, the ANN based system mimics the decisions of an expert without specifically formulating the if-then type of rules. In fact, the ANNs demonstrate their superiority when such if-then type of rules are hard to generate by human expert. Verification of traditional knowledge based system is based on the proof of consistency and completeness of the rule knowledge base and correctness of the production engine. These techniques, however, can not be directly applied to ANN based components. In this position paper, we propose a verification and validation procedure for KBS with ANN based components. The essence of this procedure is to obtain an accurate system specificatio...

Contributor: The Pennsylvania State University CiteSeer Archives

Publisher: unknown

Date: 1998-03-20

Pubyear: unknown

Format: ps

Identifier: http://citeseer.ist.psu.edu/140997.html

Source: http://research.ivv.nasa.gov/~wen/aaai96.ps

Language: en

Rights: unrestricted

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