The science of Cooperative Information Systems (CIS) synthesizes AI and database results to develop effective systems - those composed of existing, heterogeneous components within an enterprise, as well as those whose components are independently developed and designed to behave autonomously in separate enterprises. Applications of CIS include telecommunications, virtual enterprises, logistics, healthcare, and manufacturing automation, to name but a few. CIS is distinguished from other AI work in agents by involving robust database techniques for capturing and using semantics through abstractions such as data models, ontologies, transactions, relaxed transactions, and workflows.
This tutorial will present the necessary concepts, architectures, theories, techniques, and infrastructure to build cooperative information systems. It will include a comprehensive overview of the state of the art in agent applications in distributed, heterogeneous databases.
We believe a tutorial such as this one, which combines AI, databases, and distributed computing, is essential for anyone trying to quickly come up to speed on a vast research area. This tutorial will guide practitioners by describing implemented, tested agent-based approaches to large-scale information access and management. It will introduce graduate students and other researchers to a new area with lots of exciting and important problems.
Michael N. Huhns (Ph.D., South California, 1975) directs the Center for Information Technology at the University of South Carolina. He edited the books "Distributed Artificial Intelligence," volumes 1 and 2, and authored over 100 papers and reports. Dr. Huhns has served on numerous conference committees and advisory boards and is an Associate Editor for IEEE Expert and ACM Transactions on Information Systems. He serves on the editorial boards for the International Journal of Cooperative Information Systems, the Journal of Intelligent Manufacturing, and IEEE Internet Computing.