01425nas a2200205 4500008004100000245004100041210003900082260002000121300001400141520087400155100002301029700001901052700002001071700001501091700002001106700001701126700001601143700001601159856004401175 2003 eng d00aContextual Random {Boolean} Networks0 aContextual Random Boolean Networks bSpringer-Verlag a615–6243 aWe propose the use of Deterministic Generalized Asynchronous Random Boolean Networks (Gershenson, 2002) as models of contextual deterministic discrete dynamical systems. We show that changes in the context have drastic effects on the global properties of the same networks, namely the average number of attractors and the average percentage of states in attractors. We introduce the situation where we lack knowledge on the context as a more realistic model for contextual dynamical systems. We notice that this makes the network non-deterministic in a specific way, namely introducing a non-Kolmogorovian quantum-like structure for the modelling of the network (Aerts 1986). In this case, for example, a state of the network has the potentiality (probability) of collapsing into different attractors, depending on the specific form of lack of knowledge on the context.1 aGershenson, Carlos1 aBroekaert, Jan1 aAerts, Diederik1 aBanzhaf, W1 aChristaller, T.1 aDittrich, P.1 aKim, J., T.1 aZiegler, J. uhttp://uk.arxiv.org/abs/nlin.AO/030302101287nas a2200193 4500008004100000245004700041210004500088260002100133300001400154520075400168100002300922700002300945700001500968700002000983700001701003700001601020700001601036856004101052 2003 eng d00aWhen Can We Call a System Self-Organizing?0 aWhen Can We Call a System SelfOrganizing aBerlinbSpringer a606–6143 aWe do not attempt to provide yet another definition of self-organizing systems, nor review previous definitions. We explore the conditions necessary to describe self-organizing systems, inspired on decades of their study, in order to understand them better. These involve the dynamics of the system, and the purpose, boundaries, and description level chosen by an observer. We show how, changing the level or ``graining'' of description, the same system can be self-organizing or not. We also discuss common problems we face when studying self-organizing systems. We analyse when building, designing, and controlling artificial self-organizing systems is useful. We state that self-organization is a way of observing systems, not a class of systems.1 aGershenson, Carlos1 aHeylighen, Francis1 aBanzhaf, W1 aChristaller, T.1 aDittrich, P.1 aKim, J., T.1 aZiegler, J. uhttp://arxiv.org/abs/nlin.AO/0303020