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Advice generation in an axiomatically-based expert system
Abstract We distinguish axiomatically-based expert We distinguish axiomatically-based expert systems, whose design and implementation are guided by one or more axiomatically-based theories of decision-making (e.g., decision theory, Bayesian probability theory,.maximum entropy theory), from traditional expert systems. An analysis of the knowledge acquisition and computational needs of axiomatically-based expert systems is presented. An explicit quantitative comparison is made between the actual knowledge acquisition effort required to build an existing system, and the effort that would be required to build an analogous axiomatically-based advice system. The costs and benefits of the axiomatic approach are discussed. The results suggest that the additional initial costs of knowledge acquisition for the axiomatic approach are outweighed by the long-term benefits this apprach provides. long-term benefits this apprach provides.
Address Washington, DC +
Author Curtis Langlotz +
Bibtype techreport  +
Institution Knowledge Systems, AI Laboratory +
Key KSL-87-52  +
Modification dateThis property is a special property in this wiki. 1 May 2009 13:38:56  +
Number KSL-87-52  +
Tag Computer science +
Title Advice Generation in an Axiomatically-Based Expert System  +
Tr id KSL-87-52  +
Year 1987  +
Categories Technical Report, Publication, KSL Technical Report
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