Abstract
Causal Networks have recently received much attention in AI, and have been used in many areas as a knowledge representation. First, from the knowledge engineering point of view, we present causal networks, introduce a concept of network parameters, propose some principles for construction and use of causal networks, and indicate the advantages of the knowledge bases with the form of causal networks. In order to put them into practice and incorporate with other techniques in AI, we have introduced the idea of causal networks into a Knowledge System Environment (KSE) as a toolkit (Bent). Then we give an overview of KSE, followed by a detailed discussion about Bent.
This work has been supported in part by national 8∶5 programs and in part by national 863 program.
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© 1995 Springer-Verlag Berlin Heidelberg
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Liang, J., Ren, Q., Xu, Z., Fang, J. (1995). Causal Networks and their toolkit in KSE. In: Bouchon-Meunier, B., Yager, R.R., Zadeh, L.A. (eds) Advances in Intelligent Computing — IPMU '94. IPMU 1994. Lecture Notes in Computer Science, vol 945. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0035945
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DOI: https://doi.org/10.1007/BFb0035945
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