Cognitive maps have emerged as an important tool in modeling and decision making. In a nutshell they are signed di-graphs that capture the cause/effect relationships that subject matter experts believe exist in a problem space under consideration. Each node in the map represents some variable concept. These generally fall into one of several “hard” categories: physical attributes of the environment, characteristics of artifacts embedded in the problem space, or one of several “soft” areas: decisions being made, social, psychological or cultural characteristics of the decision makers, intentions, etc. Part of the value of cognitive maps is that these hard and soft concepts can be seamlessly mixed in.
