Decision analytic networks in artificial intelligence

Article Abstract:

Research literature on influence diagrams (IDs) and belief networks (BNs) are reviewed. This family of graphical models of Bayesian decision theory has been studied extensively in recent years. Researchers are excited about the two models because they are the missing links in people's understanding of practical problems within a probabilistic framework. ID and BN studies have brought together researchers in artificial intelligence (AI) and decision analysis (DA). Although the two communities are both engaged in developing formal models of human knowledge and expertise, they have historically been separated by their different approaches to this task. The emergence of IDs and BNs has given the two groups a common interest. The models are of equal significance to theoreticians, experimentalists and implementors.

Decision theory

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Inducing rules for expert system development: an example using default and bankruptcy data

Article Abstract:

The problems associated with knowledge acquisition have a central importance in the development of knowledge-based computer consulting systems for various problem domains. Research has been conducted on the effectiveness of discovering predictive knowledge structures in financial data using an inductive algorithm. The inductive algorithm's results are compared to results generated by discriminant analysis, and group and individual judgments. The predictive attributes show a partial intersection and the inductively produced knowledge structures outperform competing models.

Product development, Expert systems, Discriminant analysis, Induction (Mathematics), Mathematical induction

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Partial deductive closure: logical stimulation and management science

Article Abstract:

A model is presented for creating machines that can analyze management theories and revise them as necessary.

United States, Models, Logic design, Automated theorem proving

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