In this paper we present the dynamic cognitive network (DCN) which is an ex
tension of the fuzzy cognitive map (FCM). Each concept in the DCNs can have
its own value set, depending on how precisely it needs to be described in
the network. This enables the DCN to describe the strength of causes and th
e degree of effects that are crucial to conducting meaningful inferences. T
he arcs in the DCN define dynamic, causal relationships between concepts. S
tructurally, DNCs are scalable and more flexible as compared to FCMs. A DCN
can be as simple as a cognitive map (CM), an FCM, or as complex as a nonli
near dynamic system. To demonstrate the potential applications of DCNs, we
present some simulation results. This paper represents our first attempt to
develop a dynamic fuzzy inference system using causal relationships. There
are many interesting and challenging theoretical and practical issues in t
he DCN open to further research.