Constructing Weighted Argumentation Framework with Cognitive Maps

Cognitive map is a qualitative decision model which is frequently used in social science and decision making applications. This model allows to easily organize individuals´ judgments, thinking or beliefs about a given problem in a graphical representation containing different concepts and influences between them. However, reasoning on this model presents some limits and remains a difficult task. For example, cognitive maps do not model uncertainty within the variables, and only deductive reasoning (predicting an effect given a cause) is possible. In this paper, we show how to translate the knowledge represented in cognitive maps in the form of arguments and attack relations among them. In particular, given a decision problem, a cognitive map was first built by eliciting knowledge from experts and then transforming it in a weighted argumentation framework (WAF for short) for ensuring efficient reasoning. Another contribution of this paper concerns enriching the WAF obtained from a given cognitive map for dealing with dynamics through the consideration of a varying set of observations.