Article citationsMore>>

M. Morge and P. Mancarella, “Assumption-Based Argumentation for the Minimal Concession Strategy,” In: P. McBurney, I. Rahwan, S. Parsons and N. Maudet, Eds., Argumentation in Multi-Agent Systems (ArgMAS 2009), Vol. 6057, Springer, Berlin, 2010, pp. 114-133.

has been cited by the following article:

• TITLE: Business Intelligence Expert System on SOX Compliance over the Purchase Orders Creation Process

  AUTHORS: Jesus Angel Fernandez, Quintin Martin Martin, Juan Manuel Corchado Rodriguez

  KEYWORDS: Multiagent Systems (MAS); Decision Support Systems (DSS); Sarbanes-Oxley Act (SOX); Argumentation; Artificial Intelligence; Business Intelligence (BI); Expert Systems (ES)

  JOURNAL NAME: Intelligent Information Management, Vol.5 No.3, May 24, 2013

  ABSTRACT: The objective of this work is to define a decision support system over SOX (Sarbanes-Oxley Act) compatibility and quality of the Purchase Orders Creation Process based on Artificial Intelligence and Theory of Argumentation knowledge and techniques. This proposed model directly contributes to both scientific research artificial intelligent area and business practices. From business perspective it empowers the use of artificial intelligent models and techniques to drive decision making processes over financial statements. From scientific and research area the impact is based on the combination of 1) an Information Seeking Dialog Protocol in which a requestor agent inquires the business case, 2) a Facts Valuation based Protocol in which the previously gathered facts are analyzed, 3) the already incorporated initial knowledge of a human expert via initial beliefs, 4) the Intra-Agent Decision Making Protocol based on deductive argumentation and 5) the semi automated Dynamic Knowledge Learning Protocol. Last but not least the suggested way of integration of this proposed model in a higher level multiagent intelligent system in which a Joint Deliberative Dialog Protocol and an Inter-Agent Decision Deductive Argumentation Making Protocol are described.