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Reasoning Under Uncertainty With Dependency Information

Current techniques for dealing with uncertainty in expert systems do not adequately handle dependency information. In fact, most schemes make routine independence assumptions. These assumptions lead to serious questions as to the validity of the conclusions reached by systems which employ such schemes. This paper introduces a technique for reasoning with dependency information in expert systems that acquire probabilistic evidence. This technique relies on a modified version of Dempster-Shafer Theory. In particular, a new support function and updating scheme are used. Examples of several different types of situations are given to show that this modified technique deals with dependency in both an intuitive and reasonable way.