Vorwort

Ordnungsbildung und Erkenntnis bedingen einander. Erkenntnis setzt die Beobachtung von Ordnungsstrukturen voraus oder deren Schöpfung durch Abstraktion und Modellbildung. Beiträge aus unterschiedlichen Bereichen universitärer Forschung untersuchen Strukturen, die einen Bezug haben zu (partiell) autonomen Akteuren (beziehungsweise Agierenden, Agenten) und den dynamischen Prozessen, in denen sie entwickelt werden. Dabei ablaufende Erkenntnisprozesse erfordern interobjektiv erfahrbare, teilweise auch in Symbolik und Ritualen fassbare Ordnungsstrukturen, auch wenn diese erst simultan mit Handlungs- oder Erkenntnisprozessen entstehen. Rekursive Bezüge können zu Formen der Selbstorganisation führen. Bei höher entwickelten Strukturen können Aspekte des Wissens, Lernens (und Vergessens) einbezogen werden und zusätzlich durch emotionale Zustände verstärkt oder abgeschwächt werden. • Wie entstehen Struktur und Ordnung? • Wie werden sie stabilisiert, modifiziert, revolutioniert, restabilisiert? • Wie werden sie zerstört und aufgelöst? • Wie lässt sich das Verhältnis von Ordnung/Struktur und Wandel/Prozess fassen und (gegebenenfalls formal oder im Rechner) modellieren? • Welche institutionalisierten Mechanismen spielen dabei welche Rolle? • Wie prägen diese Mechanismen die Auseinandersetzungen zwischen Akteuren um "richtiges" und "falsches" Handeln und " richtiges" und "falsches" Wissen von diesem Handeln (Realitätsdefinitionen, Ordnungs- und Zielvorstellungen, Legitimationen)? • Welche Wechselwirkungen bestehen zwischen "stummen" Verhaltensordnungen (Handeln) und "beredter" symbolvermittelter Reflexion eben dieser Verhaltensordnungen (Reden und Wissen)? Wissenschaftlerinnen und Wissenschaftler hatten sich am 5.9.2005 an der Universität Hamburg zu einem Workshop über "Ordnungsbildung und Erkenntnisprozesse" zusammengefunden. In diesem Band sind zahlreiche der gehaltenen Beiträge gesammeltFormation of order and cognition are interdependent. Knowledge presupposes the observation of order structures or their creation through abstraction and modelling. Contributions from different areas of university research examine structures that relate to (partially) autonomous actors (or agents) and the dynamic processes in which they are developed. Processes of knowledge that take place in this context require structures of order that can be experienced interobjectively, and in some cases can also be grasped in symbolism and rituals, even if these structures are created simultaneously with processes of action or knowledge. Recursive references can lead to forms of self-organization. In more highly developed structures, aspects of knowledge, learning (and forgetting) can be included and additionally strengthened or weakened by emotional states. On November 5, 2005, scientists came together for a workshop on "Formation of Order and Knowledge Processes" at the University of Hamburg. In this volume, numerous of the given talks and articles are collected

Declarative Event-Based Workflow as Distributed Dynamic Condition Response Graphs

We present Dynamic Condition Response Graphs (DCR Graphs) as a declarative, event-based process model inspired by the workflow language employed by our industrial partner and conservatively generalizing prime event structures. A dynamic condition response graph is a directed graph with nodes representing the events that can happen and arrows representing four relations between events: condition, response, include, and exclude. Distributed DCR Graphs is then obtained by assigning roles to events and principals. We give a graphical notation inspired by related work by van der Aalst et al. We exemplify the use of distributed DCR Graphs on a simple workflow taken from a field study at a Danish hospital, pointing out their flexibility compared to imperative workflow models. Finally we provide a mapping from DCR Graphs to Buchi-automata.Comment: In Proceedings PLACES 2010, arXiv:1110.385

Concurrency in Communicating Object Petri Nets

: Objects are studied as higher-level net tokens having an individual dynamical behaviour. In the context of Petri net research it is quite natural to also model such tokens by Petri nets. To distinguish them from the system net, they are called object nets. Object nets behave like tokens, i.e., they are lying in places and are moved by transitions. In contrast to ordinary tokens, however, they may change their state (i.e. their marking) when lying in a place or when being moved by a transition. By this approach an interesting and challenging two-level system modelling technique is introduced. Similar to the object-oriented approach, complex systems are modelled close to their real appearance in a natural way to promote clear and reliable concepts. Applications in fields like workflow, agent-oriented approaches (mobile agents and/or intelligent agents as in AI research) or open system networks are feasible. This paper gives a precise definition of the basic model together with a suitab..

Petri nets for Systems Engineering : A Guide to Modeling, Verification, and Applications (China Version)

International audienc

Petri Nets for Systems Engineering : A Guide to Modeling, Verification, and Applications

International audienc