The DFKI conducts application-oriented basic research in the field of artificial intelligence and other related subfields of computer science. The overall goal is to construct systems with technical knowledge and common sense which -by using AI methods -implement a problem solution for a selected application area. Currently, there are the following research areas at the DFKI:Intelligent Engineering Systems Intelligent User Interfaces Intelligent Communication Networks Intelligent Cooperative Systems.The DFKI strives at making its research results available to the scientific community. There exist many contacts to domestic and foreign research institutions, both in academy and industry. The DFKI hosts technology transfer workshops for shareholders and other interested groups in order to inform about the current state of research.From its beginning, the DFKI has provided an attractive working environment for AI researchers from Germany and from all over the world. The goal is to have a staff of about 100 researchers at the end of the building-up phase. ; an acknowledgement of the authors and individual contributors to the work; all applicable portions of this copyright notice. Copying, reproducing, or republishing for any other purpose shall require a licence with payment of fee to Deutsches Forschungszentrum für Künstliche Intelligenz.Abstract. In the long run, the development of cooperative knowledge-based systems for complex real world domains such as production planning in mechanical engineering should yield significant economic returns. However, large investments have already been made into the conventional technology. Intelligent documentation, which abstracts the current practice of the industry, is suggested as a stepping stone for developing such knowledge-based systems. A set of coordinated knowledge acquisition tools has been developed by which intelligent documents are constructed as an intermediate product, which by itself is already useful. Within the frame of the conventional technology, the task-and domain specific hypertext structures allow the reuse of production plans while simultaneously starting the development process for knowledge based systems.
In this paper, we perform a cognitive analysis of knowledge discovery processes. As a result of this analysis, the construction-integration theory is proposed as a general framework for developing cooperative knowledge evolution systems. We thus suggest that for the acquisition of new domain knowledge in medicine, one should first construct pluralistic views on a given topic which may contain inconsistencies as well as redundancies. Only thereafter does this knowledge become consolidated into a situation-specific circumscription and the early inconsistencies become eliminated. As a proof for the viability of such knowledge acquisition processes in medicine, we present the IDEAS system, which can be used for the intelligent documentation of adverse events in clinical studies. This system provides a better documentation of the side-effects of medical drugs. Thereby, knowledge evolution occurs by achieving consistent explanations in increasingly larger contexts (i.e., more cases and more pharmaceutical substrates). Finally, it is shown how prototypes, model-based approaches and cooperative knowledge evolution systems can be distinguished as different classes of knowledge-based systems.
Knowledge assets and the learning capacity of an organization are the main sources of competitive advantage (Argyris & Schon, 1978; Prahalad & Hamel, 1990). Therefore, there is a growing interest in knowledge management (KM) and corporate memories (CM). The objectives of KM are to promote preservation, communication, and growth of knowledge in the organization (Steels, 1993). According to Fischer et al.(1997), the problem is to deliver the right knowledge at the right time to the right person in the right way. KM is a very complex problem that can be tackled from several viewpoints: socio-organizational, financial and economical, technical, human, legal (Barthès, 1996). A CM is a tool to support KM. Van Heijst et al. (1996) define a CM as an “explicit, disembodied, persistent representation of knowledge and information in an organization.” It is important to consider the development of a CM not only from a technical viewpoint. In this work the human and socio-organizational aspects play a significant role. We will focus on the following (complex) requirement that must be fulfilled by a computer-based CM:
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