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Project Leaders: Su-Shing Chen, G. Springer, A. Joshi, J. Keller and X. Zhuang, CECS
Through the advent of high performance computing and communications networks, networked computer systems have emerged to be the dominant paradigm, and information has become widely available in digital formats, creating the phenomenon of information glut or information overload. Computational intelligence will be useful to reduce the information overload and to build the next-generation, more efficient, networked information systems.
The MINIS Project intends to explore this new frontier of intelligent networked information systems by integrating computational intelligence methodologies and networked information. The project is the research and development of a "vBNS-based knowledge network" - a collaborative information environment for the learning, managing, reasoning, and visualizing of a broad spectrum of networked multimedia information.
We will develop networked information technology research by extending computational intelligence methodologies from a single computer platform to a large-scale, intelligent, networked information system. We have done extensive research in fuzzy logic, neural networks, and cognitive maps. The main task is to combine and integrate these computationally intelligent algorithms, and to extend them further to distributed computational intelligence in the general framework of networked information systems. The MINIS Project will include a large number of heterogeneous information and knowledge bases managed by a host of intelligent agents distributed over a large computer and communications network. Intelligent agents may be humans, humans interacting with computers, humans working with computer support, and computer systems performing tasks with or without human intervention. Intelligent, networked information systems are evolved from several disjoint technologies such as databases, computational intelligence, natural language processing, and computer networks. It is easy to imagine the benefits of powerful knowledge base systems (e.g., medical diagnostic systems) with efficient access to several large information bases, and of large databases (e.g. airline reservation systems) with added intelligence (e.g. scheduling and re-scheduling travel reservations considering individual's preferences). The MINIS Project will be considerably more powerful than such extrapolations of existing system concepts.
The design and evolution of the MINIS Project will require the extension and integration of several technologies (databases, computational intelligence, computer networks, etc.). Database systems will supply information management techniques, particularly for distributed databases, as well as efficient implementation techniques for information bases. Computational intelligence will contribute distributed problem solving, knowledge representation and reasoning techniques. The vBNS network connection will provide the necessary underlying communications and interconnections bandwidth for the "knowledge network".
In order to provide a viable test bed for the MINIS knowledge network, our collaboration with other MU research groups will provide the necessary large collections of digital patient records (with names and identities removed), on-line stock market data, and medical images to be tested in a distributed, network-based environment. Our collaborators include the Department of Healthcare Information Systems, College of Business and Public Administrations, and College of Veterinary Medicine. There are also several ongoing collaborative projects between the MINIS group and the University of Illinois at Urbana-Champaign, University of Florida at Gainesville, and University of Maryland at College Park. We need the vBNS connection to communicate, for example, 3-D rapid prototyping design files, interactive video and audio files, and networked knowledge reasoning. Technical issues such as network data volumes, latency and scalability in addition to the issues of computational intelligence and user interaction can be actively measured in the MINIS test bed.
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