Abstract — In this paper I sketch a rough taxonomy of self-organization which may be of relevance in the study of cognitive and biological systems. I frame the problem both in terms of the language of secondorder cybernetics as well as the language of current theories of self-organization and complexity. The goal of establishing such a taxonomy is to allow for a classification of different tools used both in Artificial Intelligence and Artificial Life, so that different aspects of cognitive and biological systems may be incorporated in more accurate models of such systems. In particular, I defend, on the one hand, that self-organization alone is not rich enough for our intended simulations, and on the other, that genetic selection in biology and symbolic representation in cognitive science alone leave out the very important (self-organizing) characteristics of particular embodiments of evolving and learning systems.

I. Historical Development of Cybernetics....................................................... 1 A. Origins..................................................................................... 1 B. Second Order Cybernetics............................................................ 2

Zadeh’s Fuzzy Sets are extended with the Dempster-Shafer Theory of Evidence into a new mathematical structure called Evidence Sets, which can capture more efficiently all recognized forms of uncertainty in a formalism that explicitly models the subjective context dependencies of linguistic categories. A belief-based theory of Approximate Reasoning is proposed for these structures. Evidence sets are then used in the development of a relational database architecture useful for the data mining of information stored in several networked databases. This useful data mining application establishes an Artificial Intelligence model of Cognitive Categorization with a hybrid architecture that possesses both connectionist and symbolic attributes.

Abstract. According to the standard definition of anticipatory systems, anticipation is based on a predictive model of the system itself and its environment. The paper abandons this perspective of weak anticipation in favor of what has been called strong anticipation. It is proposed that anticipation is a consequence of canalization caused by the organization of the structural building-blocks of which the system in question consists. Strong anticipation can account for the anticipatory behavior in animals to which we would not impute the ability of creating internal models of themselves. 1

Autonomous agents have become an influential and powerful paradigm in a great variety of disciplines, from sociology and economics to distributed artificial intelligence and software engineering to philosophy. Given that the paradigm has been around for awhile, one would expect a broadly agreed-upon, solid understanding of what autonomous agents are and what they are not. This, however, is not the case. We therefore join the ongoing debate on what are the appropriate notions of autonomous agency. We approach agents and agent ontology from a cybernetics and general systems perspective, in contrast to the much more common in the agent literature sociology, anthropology and/or cognitive psychology based approaches. We attempt to identify the most fundamental attributes of autonomous agents, and propose a tentative hierarchy of autonomous agents based on those attributes.

. An architecture for the implementation of possibilistic models in an object-oriented programming environment (C++ in particular) is described. Fundamental classes for special and general random sets, their associated fuzzy measures, special and general distributions and fuzzy sets, and possibilistic processes are specified. Supplementary methods---including the fast Mobius transform, the maximum entropy and Bayesian approximations of random sets, distribution operators, compatibility measures, consonant approximations, frequency conversions, and possibilistic normalization and measurement methods---are also introduced. Empirical results to be investigated are also described. 1 Introduction Possibility theory [4] is an alternative information theory to that based on probability. Although possibility theory is logically independent of probability theory, they are related: both arise in Dempster-Shafer evidence theory as fuzzy measures defined on random sets; and their distributions a...

Abstract. Handshaking between product management and R&D is key to the success of product development projects. Traditional requirements engineering processes build on good quality requirements specifications, which typically are not achievable in practical circumstances, especially not in distributed development where daily communication cannot easily be achieved to support the understanding of the specification and tacit knowledge cannot easily be spread. Projects thus risk misunderstanding requirements and are likely to deliver inadequate solutions. This paper presents an approach that uses downstream engineering artifacts, design decisions, to improve upstream information, a project’s requirements. During its preliminary validation, the approach yielded promising results. It is well suited for distributed software projects, where the negotiation on requirements and solution design need to be made explicit and potential problems and misunderstandings caught at early stages. 1

Mathematical systems theory suggests structures which are useful for representing cyberspatial and hypertextual systems. In particular, we introduce semantic webs based on acyclic multirelational systems as a model for typed link hypertexts. Such semantic webs are like semantic networks where concepts participate in a semantic category only in one direction. The resulting structures have indirect cyclicity in virtue of their multiple, overlapping loose hierarchies. Furthermore, they map easily into both existing and proposed hypertext systems, and resonate with many of the key ideas in Systems Science. 1 Introduction As Cybernetics and Systems Science (which we here simply call Systems Science) move into their second half-century, the computer technologies that underlie them and finally allow their full expression are also coming of age. The continued exponential growth of computer technology is well known. As evolutionary theory suggests, such vast quantitative change is apt to resu...

The objective of this paper is to introduce fuzzy set theory and develop fuzzy mathematical models to assess sustainable development based on context-dependent economic, ecological, and societal sustainability indicators. Membership functions are at the core of fuzzy models, and define the degree to which indicators contribute to development. Although a decision-making process regarding sustainable development is subjective, fuzzy set theory links human expectations about development, expressed in linguistic propositions, to numerical data, expressed in measurements of sustainability indicators. In the future, practical implementation of such models will be based on elicitation of expert knowledge to construct a membership function. The fuzzy models developed in this paper provide a novel approach to support decisions regarding sustainable development. 5001-6182 Business 5201-5982 Business Science Library of Congress Classification (LCC) QA 76.9 Fuzzy sets M Business Ad...

A conceptual analysis of controls and models from a semiotic perspective is provided with the goal of elucidating their nature in complex systems. Atomic control systems and models are described as the paradigmatic forms of systems in relation to their environments. While they share measurement relations, they differ topologically in that control systems are circularly and models linearly related related to their environments. Computation is then introduced in control systems, which motivates hierarchical decompositions and hybrid modeling and control systems. The various relations in complex control systems and models are placed in a semiotic context in terms of constraint relations among various entities, where rules and laws are distinguished as contingent and necessary entailments respectively. Finally selection as a meta-level of constraint is introduced as the necessary condition for semantic relations in control systems and models. 1 Introduction We are interested in understand...