Contents I Introduction
Cognitive Map (CM) is proposed by Axelrod [1] for visualizing causal relationships among factors to facilitate human cognitive thinking. CM uses binary concepts to model important factors and binary links to model their causal relationships. A CM can be viewed as a tuple, $${\rm M}=<{\bf V},\ {\bf A}>,$$ where is the set of vertices representing the concepts and is the set of arcs representing the causal relationships among concepts. $$\eqalign{{\bf V}=&\{< v_{1}, f_{v_{1}}, \ {\rm S}(v_{1}) >,\ < v_{2}, f_{v_{2}},\ {\rm S}(v_{2})>,\cr &\qquad\qquad\ldots, < v_{n}, f_{v_{n}},\ {\rm S}(v_{n}) > \},\cr{\bf A}=&\{ < a(v_{i},\ v_{j}),\ w(a(v_{i},\ v_{j})) > \vert v_{i},\ v_{j}\in {\bf V}\ \}, {}}$$
This paper does not differentiate and .
For simplicity, we do not differentiate from when there is no ambiguity.
where are the vertices (concepts), is the number of concepts, is the arc from to is the weight of arc ; it can also be written as or . In CM, indicates a negative causal relationship; represents a positive causal relationship; 0 means no causal relationship exist.