Self-organization is defined and several examples which motivate this definition are presented. The significance of this definition is explored by comparison with the metrization problem discussed in the companion paper (1) and it is seen that self-organization requires decomposing the space representing the environment. In the absence of a priori knowledge of the environment, the self-organizing machine must resort to a sequence of projections on unit spheres to effect this decomposition. Such a sequence of projections can be provided by repeated use of a nilpotent projection operator (NPO). An analog computer mechanization of one such NPO is discussed and the signal processing behavior of the NPO is presented in detail using the Euclidean geometrical representation of the metrizable topology provided in the companion paper. Self-organizing systems using multiple NPO’s are discussed and current areas of research are identified. INTRODUCTION Unlike the companion paper which considers certain questions in depth, this paper presents a survey of the scope of our work in self-organizing systems and is not intended to be profound. The approach we have followed may be called phenomenological (Figure 1). That is, the desired behavior (self-organization) was defined, represented mathematically, and a mechanism(s) required to yield the postulated behavior was synthesized using mathematical techniques. One advantage of this approach is that it avoids assumptions of uniqueness of the mechanism. Another advantage is that the desired behavior, which is after all the principal objective, is taken as invariant. An obvious disadvantage is the requirement for the aforementioned synthesis technique; fortunately in our case a sufficiently general technique had been developed by the author of the companion paper. From the foregoing and from the definition of self-organization we employ (see conceptual model), it would appear that our research does not fit comfortably within any of the well publicized approaches to self-organization (2). Philosophically, we lean toward viewpoints expressed by Ashby (3), (4), Hawkins (5), and Mesarovic (6) but with certain reservations. We have avoided the neural net approach partly because it is receiving considerable attention and also because the brain mechanism need not be the unique way to produce the desired behavior. [Illustration: Figure 1—Approach used in Nortronics research on self-organizing systems]