Verification and Validation of Agent Based Simulations using the VOMAS (Virtual Overlay Multi-agent System) Approach

—Agent Based Models are very popular in a number of different areas. For example, they have been used in a range of domains ranging from modeling of tumor growth, immune systems, molecules to models of social networks, crowds and computer and mobile self-organizing networks. One reason for their success is their intuitiveness and similarity to human cognition. However, with this power of abstraction, in spite of being easily applicable to such a wide number of domains, it is hard to validate agent-based models. In addition, building valid and credible simulations is not just a challenging task but also a crucial exercise to ensure that what we are modeling is, at some level of abstraction, a model of our conceptual system; the system that we have in mind. In this paper, we address this important area of validation of agent based models by presenting a novel technique which has broad applicability and can be applied to all kinds of agent-based models. We present a framework, where a virtual overlay multi-agent system can be used to validate simulation models. In addition, since agent-based models have been typically growing, in parallel, in multiple domains, to cater for all of these, we present a new single validation technique applicable to all agent based models. Our technique, which allows for the validation of agent based simulations uses VOMAS: a Virtual Overlay Multi-agent System. This overlay multi-agent system can comprise various types of agents, which form an overlay on top of the agent based simulation model that needs to be validated. Other than being able to watch and log, each of these agents contains clearly defined constraints, which, if violated, can be logged in real time. To demonstrate its effectiveness, we show its broad applicability in a wide variety of simulation models ranging from social sciences to computer networks in spatial and non-spatial conceptual models

Communication in organizations: the heart of information systems

We propose a theory characterizing information systems (IS) as language communities which use and develop domain-specific languages for communication. Our theory is anchored in Language Critique, a branch of philosophy of language. In developing our theory, we draw on Systems Theory and Cybernetics as a theoretical framework. "Organization" of a system is directly related to communication of its sub-systems. "Big systems" are self-organizing and the control of this ability is disseminated throughout the system itself. Therefore, the influence on changes of the system from its outside is limited. Operations intended to change an organization are restricted to indirect approaches. The creation of domain-specific languages by the system itself leads to advantageous communication costs compared to colloquial communication at the price of set-up costs for language communities. Furthermore, we demonstrate how our theoretical constructs help to describe and predict the behavior of IS. Finally, we discuss implications of our theory for further research and IS in general. Keywords: Language Critique, language communities, communication, self-organization, IS researc

Feminist Ecological Economics

This article provides an overview of feminist ecological economics, with special attention to three particular aspects: its theoretical foundations and relation to other schools of thought, its implications for activism and public policy, and directions for future research work.This research was supported by the Social Sciences and Humanities Research Council of Canad

Emergence of scaling in random networks

Systems as diverse as genetic networks or the world wide web are best described as networks with complex topology. A common property of many large networks is that the vertex connectivities follow a scale-free power-law distribution. This feature is found to be a consequence of the two generic mechanisms that networks expand continuously by the addition of new vertices, and new vertices attach preferentially to already well connected sites. A model based on these two ingredients reproduces the observed stationary scale-free distributions, indicating that the development of large networks is governed by robust self-organizing phenomena that go beyond the particulars of the individual systems.Comment: 11 pages, 2 figure

Towards adaptive multi-robot systems: self-organization and self-adaptation

Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG geförderten) Allianz- bzw. Nationallizenz frei zugänglich.This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.The development of complex systems ensembles that operate in uncertain environments is a major challenge. The reason for this is that system designers are not able to fully specify the system during specification and development and before it is being deployed. Natural swarm systems enjoy similar characteristics, yet, being self-adaptive and being able to self-organize, these systems show beneficial emergent behaviour. Similar concepts can be extremely helpful for artificial systems, especially when it comes to multi-robot scenarios, which require such solution in order to be applicable to highly uncertain real world application. In this article, we present a comprehensive overview over state-of-the-art solutions in emergent systems, self-organization, self-adaptation, and robotics. We discuss these approaches in the light of a framework for multi-robot systems and identify similarities, differences missing links and open gaps that have to be addressed in order to make this framework possible