A Distributed Intelligence Paradigm for Knowledge Management

Matteo Bonifacio, Paolo Bouquet, and Alberto Manzardo

In the last ten years, knowledge management (KM) has become a new fashioned managerial practice. Though KM theories seem to benefit from a "contamination" with cognitive and social sciences, which emphasize a subjective, contextual, and distributed approach to knowledge representation and integration, current technologies support what we may call a "god’s eye" paradigm, ill which knowledge is viewed as an objective resource. In this paper we discuss artificial intelligence theories and technologies that can support a shift to a new paradigm, called the "distributed intelligence" paradigm, in designing KM systems. Using the cvolution of KM systems within Arthur Andersen Consulting as a motivating case study, we propose the framework of MultiContext Systems as a specification language for distributed intelligence KM systems, and sketch an agent-based architecture as an example of a KM system which embodies the assumptions of the distributed intelligence paradigm.

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