Framework for Modeling the Cognitive Process

Information is key to command and control. Yet information alone is not enough; information is neither the problem nor the solution when it comes to issues of command and control. Use of information is essential. That which is commonly called “information” generically exists in many forms, with each form having temporal implications. Furthermore, with so much information readily available and increasingly so, we must develop better ways to combat information overload. Interestingly, the cognitive process itself sheds much light on problems facing the information age and can provide insight into what is going on with information at a fundamental level. In considering such a process, one should examine where information comes from, where it is going, what it’s nature is and how it is used. This paper describes a signal-based perspective of information and how signals in general fuel the cognitive process. More significantly, we introduce a novel framework for conceptualizing the cognitive process. We describe cognition and related topics at a high level and in simple terms using ordinary language. Yet seemingly simple concepts, when combined and viewed a certain way, can take on significant meaning. We present the concept of abstraction as one of two dimensions in our framework. Here abstraction is viewed overall as a function of space or form, with signals ranging anywhere from concrete to abstract. At one end of this spectrum are physical signals, for instance ones which are tangible and may readily be perceived by the senses. At the other end of the spectrum are abstract signals, for instance ones which may be conceived or realized by the mind but lack physical form. The second dimension in our framework represents time. Here the concept of generalization is portrayed overall as being a function of time or frequency, with signals ranging anywhere from data (time-sensitive, high frequency and least organized) to information to knowledge (time-insensitive, infrequently changing and most organized). In this dimension, signals tend to flow from many pieces of specific data (i.e., details) to fewer items having more significance (i.e., general knowledge). We combine the concepts of abstraction and generalization within our approach to form a unique perspective of the cognitive process, with information at the core, suggesting that this perspective may facilitate the modeling of cognition.