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Artificial Intelligence Techniques for Rational Decision Making pp 111–130Cite as

Filtering Irrelevant Information for Rational Decision Making

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Part of the book series: Advanced Information and Knowledge Processing ((AI&KP))

Abstract

This chapter deals with the concept of using relevant information as a basis of rational decision making. In this regard, whenever information is irrelevant it needs to be marginalized or eliminated. Making decisions using information which contains irrelevant information often confuses a decision making process. In this chapter we discuss four methods for making rational decisions by either marginalizing irrelevant information or not using irrelevant information. These methods are marginalization of irrationality approach, automatic relevance determination, principal component analysis and independent component analysis. These techniques are applied to condition monitoring, credit scoring, interstate conflict and face recognition.

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Authors and Affiliations

  1. Faculty of Engineering and the Built Enviroment, University of Johannesburg, Auckland Park, South Africa

    Tshilidzi Marwala

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  1. Tshilidzi Marwala
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Correspondence to Tshilidzi Marwala .

Conclusions

Conclusions

This chapter studied methods that are used for dealing with irrelevant information. Four techniques were considered and these were the marginalization of irrationality approach, automatic relevance determination , principal component analysis and independent component analysis . These techniques were applied to the problems of condition monitoring, credit scoring, interstate conflict and face recognition and were found to be effective on handling irrelevant information.

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Marwala, T. (2014). Filtering Irrelevant Information for Rational Decision Making. In: Artificial Intelligence Techniques for Rational Decision Making. Advanced Information and Knowledge Processing. Springer, Cham. https://doi.org/10.1007/978-3-319-11424-8_7

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  • DOI: https://doi.org/10.1007/978-3-319-11424-8_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11423-1

  • Online ISBN: 978-3-319-11424-8

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