The full text of this article
Foundations for an intelligent business logic engine using genetic programming and RuleML-based services
by Garnett Wilson, Malcolm I. Heywood
International Journal of Business Process Integration and Management (IJBPIM), Vol. 2, No. 4, 2007
Abstract: Service Oriented Architectures (SOAs) involve interacting business applications loosely interconnected by published services. In business environments, the content of these published services is in a constant state of change. A natural choice for the automatic synthesis and response to constantly changing service logic is an inherently adaptive, or evolutionary, system. This paper proposes and provides the design foundation for an automatic RuleML-based business rule recommendation engine using Genetic Programming (GP). The system proposed would actively adapt to rules exposed as web services from internal or external providers in order to automatically produce rule-based recommendations for the competitive advantage of the enterprise. This paper assumes the use of RuleML as the language used to communicate the services between providers, and describes the process whereby the rules can be translated and encoded for analysis in a GP system. Following encoding, the implementation details whereby the algorithm would automatically evaluate and generate new RuleML-based recommendations are described.
Online publication date: Tue, 01-Apr-2008
is only available to individual subscribers or to users at subscribing institutions.
Go to Inderscience Online Journals to access the Full Text of this article.
Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.
Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Business Process Integration and Management (IJBPIM):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable).
See our Orders page to subscribe.
If you still need assistance, please email firstname.lastname@example.org