Hierarchical representation of complex systems for supporting human decision making

Complex systems models for strategic decision making

A number of simulation techniques may be applied to strategy and decision-making. In using such techniques it is important to understand the role of models, in the context of the wider decision-making process which is largely a communal and political process; the choice of a particular approach or technique depends not only on the type of decision being considered, but also on the stage of the ...

A Framework for Emotion-aware Recommender Systems supporting Decision Making

On Shared Situation Awareness for Supporting Human Decision-Making Teams

One of the challenging issues in homeland security area is the early detection and successful processing of potential terrorist threats, which demands effective team collaboration. In this research we investigate the way of incorporating naturalistic decision making models for supporting distributed team decision making. By extending Klein’s Recognition-Primed Decision model, we propose a Colla...

Using Hierarchical Recurrent Neuro-Fuzzy Systems for Decision Making

Over the last years, a number of methods have been proposed to automatically learn and optimize fuzzy rule bases from data. The obtained rule bases are usually robust and allow an interpretation even for data sets that contains imprecise or uncertain information. However, most of the proposed methods are still restricted to learn and/or optimize single layer feed-forward rule bases. The main di...

A graphical representation of uncertainty in complex decision making

The analysis of types of uncertainty and how they affect decision making in complex settings can be considerably simplified by addressing three core questions: how uncertain we are, how aware we are of uncertainty and how context and perception affect uncertainty. The continuum nature of the answers to these questions leads naturally to represent uncertainty in a 3D level-awareness-perception p...