Abstract

The issue of knowledge sharing has permeated the field of distributed AI and, in particular, its successor, multiagent systems. Through the years, many research and engineering efforts have tackled the problem of encoding and sharing knowledge without the need for a single, centralized knowledge base. The proposed solutions to this problem are based, more or less, on stringent assumptions, such as static, shared ontological models, or the existence of a common blackboard (or Linda Space) environment where entities can share knowledge. However, the uptake of the World Wide Web and the emergence of modern computing paradigms, such as distributed, open systems, have highlighted the importance of sharing distributed and heterogeneous knowledge on a larger scale-possibly on the scale of the Internet.

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