Intelligent computational argumentation for evaluating performance scores in multi-criteria decision making

Abstract

Multi Criteria Decision Making (MCDM) is a discipline aimed at assisting multiple stakeholders in contemplating a decision paradigm in an uncertain environment. The decision analysis to be performed involves numerous alternative positions assessed under varied criterion. A performance score is assigned for each alternative in terms of every criterion and it represents satisfaction of the criteria by that alternative. In a collaborative decision making environment, performance scores are either obtained when a consensus can be reached among stakeholders on a particular score or in some cases or controversial when stakeholders do not agree with each other about them. In the previous research an intelligent argumentation system for collaborative decision making was developed. In this thesis; its use is being extended for evaluating performance scores in MCDM. A framework is laid out for using the Intelligent Argumentation approach for resolving controversial performance scores. An application case study of Selection of a Mine Detection Simulation tool is used to illustrate the method. To validate it empirically, a case study to determine division of effort between software quality assurance and software testing, which has a group of 24 stakeholders, is conducted in a hypothetical setup. Its empirical data is collected and analyzed. The analysis serves two basic purposes: 1) to validate capability of the argumentation process in determining the controversial performance scores in MCDM using our intelligent computational argumentation system and to show its effectiveness in capturing rationales of stakeholders and assisting rapid collaborative decision making --Abstract, page iii