A computerized interactive technique for mapping influence diagrams (MIND)

Abstract

A computerized interactive technique for mapping influence diagrams is presented. The technique can be used to elicit influence diagrams for large, complex business policy and planning problems, to map the diagrams, to encode more information in the diagrams than is possible with traditional techniques, and to do so systematically and efficiently. The technique can reduce the cognitive strain associated with mapping influence diagrams. At the same time it can improve the efficiency of interpretation and use of the diagrams.

Multi-agent knowledge integration mechanism using particle swarm optimization

“…One example is in the field of administrative sciences, in which many decision variables and uncontrollable variables are causally interrelated (Eden & Ackermann, 1989). FCMs have been used for geographical information systems (Liu & Satur, 1999), the design of electronic commerce web sites (Lee & Lee, 2003), R&D project selection (Salmeron, 2009), knowledge management (Noh et al, 2000), bosphorus crossing problems (Ulengin et al 2001), wayfinding processes (Chen & Stanney,1999), decision analysis (Zhang et al, 1989), business process 5 redesign (Kwahk & Kim, 1999), business process analysis and reengineering (Xirogiannis and Glykas, 2004), complex war games (Klein & Cooper,1982), strategic planning problems (Ramaprasad & Poon, 1985), software operations support (Nelson et al, 2000), information retrieval (Johnson & Briggs ,1994), decision support systems (Stylios et al, 2008;Mateou and Andreou, 2008), and distributed decision-process modeling (Zhang et al, 1994). Similar to our research project, FCMs have been utilized to support group decisions.…”

A soft knowledge modeling approach for geographically dispersed financial organizations

“…Research [2] and [43] have used FCM for representing tacit knowledge in political and social analysis. FCMs have been successfully applied to various fields such as decision making in complex war games [25], strategic planning [11,44], information retrieval [20] and distributed decision process modeling [53]. Research like [30] has successfully applied FCMs to infer rich implications from stock market analysis results.…”

Using Fuzzy Cognitive Maps as a Decision Support System for Political Decisions

“…This means that they lead to decrease in the case where an increase is introduced in the cycle. Negative cycles are also called deviation counteracting cycles [18], inhibiting cycles [17] or virtuous cycles [19], [18], [20]. An example of a negative/virtuous cycle is that of C1 (Albanian insurgents actions in FYROM) !…”