Deriving Epistemic Conclusions from Agent Architecture

One of our most resilient intuitions is that causality is a precondition for information flow: where there are no causal connections, we expect there to be no flow of information. In this paper, we study this idea as it arises in the computer science notion of systems architectures, which are high level designs that describe the coarse structure of a system in terms of its high-level components and their permitted causal interactions.Engineering and Applied Science

Knowledge hubs and knowledge clusters: Designing a knowledge architecture for development.

With globalisation and knowledge-based production, firms may cooperate on a global scale, outsource parts of their administrative or productive units and negate location altogether. The extremely low transaction costs of data, information and knowledge seem to invalidate the theory of agglomeration and the spatial clustering of firms, going back to the classical work by Alfred Weber (1868-1958) and Alfred Marshall (1842-1924), who emphasized the microeconomic benefits of industrial collocation. This paper will argue against this view and show why the growth of knowledge societies will rather increase than decrease the relevance of location by creating knowledge clusters and knowledge hubs. A knowledge cluster is a local innovation system organized around universities, research institutions and firms which successfully drive innovations and create new industries. Knowledge hubs are localities with high internal and external networking and knowledge sharing capabilities. Both form a new knowledge architecture within an epistemic landscape of knowledge creation and dissemination, structured by knowledge gaps and areas of low knowledge intensity. The paper will focus on the internal dynamics of knowledge clusters and knowledge hubs and show why clustering takes place despite globalisation and the rapid growth of ICT. The basic argument that firms and their delivery chains attempt to reduce transport (transaction) costs by choosing the same location is still valid for most industrial economies, but knowledge hubs have different dynamics relating to externalities produced from knowledge sharing and research and development outputs. The paper draws on empirical data derived from ongoing research in the Lee Kong Chian School of Business, Singapore Management University and in the Center for Development Research (ZEF), University of Bonn, supported by the German Aeronautics and Space Agency (DLR).

Knowledge Clusters and Knowledge Hubs: Designing Epistemic Landscapes for Development

With globalization and knowledge-based production, firms may cooperate on a global scale, outsource parts of their administrative or productive units and negate location altogether. The extremely low transaction costs of data, information and knowledge seem to invalidate the theory of agglomeration and the spatial clustering of firms, going back to the classical work by Alfred Weber and Alfred Marshall, who emphasized the microeconomic benefits of industrial collocation. This paper will argue against this view and show why the growth of knowledge societies will rather increase than decrease the relevance of location by creating knowledge clusters and knowledge hubs, due to sharing of tacit knowledge and research and development outputs. Designing epistemic landscapes of knowledge clusters and hubs is, therefore, proposed as a viable development policy.knowledge governance; knowledge cluster; knowledge hub; epistemic landscape; development

An Architectural Approach to Ensuring Consistency in Hierarchical Execution

Hierarchical task decomposition is a method used in many agent systems to organize agent knowledge. This work shows how the combination of a hierarchy and persistent assertions of knowledge can lead to difficulty in maintaining logical consistency in asserted knowledge. We explore the problematic consequences of persistent assumptions in the reasoning process and introduce novel potential solutions. Having implemented one of the possible solutions, Dynamic Hierarchical Justification, its effectiveness is demonstrated with an empirical analysis

Knowledge hubs and knowledge clusters: Designing a knowledge architecture for development.

With globalisation and knowledge-based production, firms may cooperate on a global scale, outsource parts of their administrative or productive units and negate location altogether. The extremely low transaction costs of data, information and knowledge seem to invalidate the theory of agglomeration and the spatial clustering of firms, going back to the classical work by Alfred Weber (1868-1958) and Alfred Marshall (1842-1924), who emphasized the microeconomic benefits of industrial collocation. This paper will argue against this view and show why the growth of knowledge societies will rather increase than decrease the relevance of location by creating knowledge clusters and knowledge hubs. A knowledge cluster is a local innovation system organized around universities, research institutions and firms which successfully drive innovations and create new industries. Knowledge hubs are localities with high internal and external networking and knowledge sharing capabilities. Both form a new knowledge architecture within an epistemic landscape of knowledge creation and dissemination, structured by knowledge gaps and areas of low knowledge intensity. The paper will focus on the internal dynamics of knowledge clusters and knowledge hubs and show why clustering takes place despite globalisation and the rapid growth of ICT. The basic argument that firms and their delivery chains attempt to reduce transport (transaction) costs by choosing the same location is still valid for most industrial economies, but knowledge hubs have different dynamics relating to externalities produced from knowledge sharing and research and development outputs. The paper draws on empirical data derived from ongoing research in the Lee Kong Chian School of Business, Singapore Management University and in the Center for Development Research (ZEF), University of Bonn, supported by the German Aeronautics and Space Agency (DLR).knowledge; knowledge and development; industrial agglomeration; knowledge hub; cluster; space

Modal logics are coalgebraic

Applications of modal logics are abundant in computer science, and a large number of structurally different modal logics have been successfully employed in a diverse spectrum of application contexts. Coalgebraic semantics, on the other hand, provides a uniform and encompassing view on the large variety of specific logics used in particular domains. The coalgebraic approach is generic and compositional: tools and techniques simultaneously apply to a large class of application areas and can moreover be combined in a modular way. In particular, this facilitates a pick-and-choose approach to domain specific formalisms, applicable across the entire scope of application areas, leading to generic software tools that are easier to design, to implement, and to maintain. This paper substantiates the authors' firm belief that the systematic exploitation of the coalgebraic nature of modal logic will not only have impact on the field of modal logic itself but also lead to significant progress in a number of areas within computer science, such as knowledge representation and concurrency/mobility