An Operational Semantics for Knowledge Bases
نویسندگان
چکیده
The standard approach in AI to knowledge representation is to represent an agent’s knowledge symbolically as a collection of formulas, which we can view as a knowledge base. An agent is then said to know a fact if it is provable from the formulas in his knowledge base. Halpern and Vardi advocated a model-theoretic approach to knowledge representation. In this approach, the key step is representing the agent’s knowledge using an appropriate semantic model. Here, we model knowledge bases operationally as multi-agent systems. Our results show that this approach offers significant advantages.
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تاریخ انتشار 1994