Causal knowledge and reasoning by cognitive maps: Pursuing a holistic approach
Due to the lack of an integral study about cognitive maps (CM) that focus on the causal phenomenon, this paper introduces the underlying concepts towards a holistic conceptual model, enhanced by a profile of several versions. We illustrate the use of CM through their application into the Web-based Education Systems (WBES). From the causal perspective, CM depict and simulate the systems dynamics based upon qualitative knowledge about a specific domain. A CM is a visual digraph that identifies the concepts of a given subject of analysis. CM show causal-effect relationships among the concepts and outline complex structures. This tool aims to predict the evolution of a model through causal inference. This kind of inference estimates the degree of significance of change of the concepts in the context of the whole system. The behavior of a CM is given away during iterations that update the variation of the concept state values until reach a stable point in a search space, a pattern of states or a chaotic region. The purpose of this research is to share its findings, depict the work done and promote the use of CM in a broad spectrum of domains.
causality cognitive maps concepts causal inference causal relations qualitative model