Adaptive Business Intelligence

Citation

Howard, W.R. (2007), "Adaptive Business Intelligence", Kybernetes, Vol. 36 No. 3/4, pp. 549-549. https://doi.org/10.1108/03684920710747165

It is always encouraging before taking up a book to learn something about its authors. This text we are told is written by authors who have considerable academic backgrounds in artificial intelligence (AI) and its related fields as well as years of practical experience in business and in industry. From the outset they are aware that in dealing with the field of adaptive business intelligence systems they need to discuss both prediction as well as optimisation techniques. It is the combination of these techniques that will help decision makers who are working with both complex and rapidly changing environments. To do this they have aimed in their book to introduce and explain what they term “the science and application of numerous prediction and optimisation techniques” Thereafter, they set out to show how these concepts have the potential to be used in the development of adaptive systems. The techniques they have chosen include:

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  Linear regression.

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  Decision trees and tables.

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  Genetic programming.

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  Genetic algorithms.

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  Tabu search.

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  Agent‐based modelling.

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  Time‐series forecasting.

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  Artificial neural networks.

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  Fuzzy systems.

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  Simulated annealing.

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  Ant systems.

Obviously in a book of some 200 pages the coverage of these topics, some of which could well be the subject of many books are covered only in relation to their application in adaptive systems and their measure of importance in their development.

(Section Editor's note: see also the review/report in Kybernetes, Vol. 36 No. 1, 2007)