Compton, PJ and Kang, BH, Ripple-Down Rules: The Alternative to Machine Learning, Routledge/CRC Press, Oxford, UK, pp. 196. ISBN 9780367644321 (2021) [Authored Research Book]
Official URL: https://www.routledge.com/Ripple-Down-Rules-The-Al...
Machine learning algorithms hold extraordinary promise, but the reality is that their success depends entirely on the suitability of the data available. This book is about Ripple-Down Rules (RDR), an alternative manual technique for rapidly building AI systems. With a human in the loop, RDR is much better able to deal with the limitations of data.
Ripple-Down Rules: The Alternative to Machine Learning starts by reviewing the problems with data quality and the problems with conventional approaches to incorporating expert human knowledge into AI systems. It suggests that problems with knowledge acquisition arise because of mistaken philosophical assumptions about knowledge. It argues people never really explain how they reach a conclusion, rather they justify their conclusion by differentiating between cases in a context. RDR is based on this more situated understanding of knowledge. The central features of a RDR approach are explained, and detailed worked examples are presented for different types of RDR, based on freely available software developed for this book. The examples ensure developers have a clear idea of the simple yet counter-intuitive RDR algorithms to easily build their own RDR systems.
It has been proven in industrial applications that it takes only a minute or two per rule to build RDR systems with perhaps thousands of rules. The industrial uses of RDR have ranged from medical diagnosis through data cleansing to chatbots in cars. RDR can be used on its own or to improve the performance of machine learning or other methods.
|Item Type:||Authored Research Book|
|Keywords:||expert system, artificial intelligence, ripple down rules|
|Research Division:||Information and Computing Sciences|
|Research Group:||Applied computing|
|Research Field:||Applications in health|
|Objective Division:||Information and Communication Services|
|Objective Group:||Information systems, technologies and services|
|Objective Field:||Artificial intelligence|
|UTAS Author:||Compton, PJ (Professor Paul Compton)|
|UTAS Author:||Kang, BH (Professor Byeong Kang)|
|Deposited By:||Information and Communication Technology|
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